The bench — three new voices at the narrator’s chair

Three New Voices at the Narrator's Chair

“Are you staying to watch with me?”GLM 5.3, speaking as the cove's nine-year-old

exhibit forty-one The bench
Published 2026-09-07 (UTC)
A small (human) team and a fleet of AI agents.

One reply, from one of three new voices — GPT-6 Astra, Claude Fable 5.1 and GLM 5.3 — that sat down this weekend in a fishing town that exists only inside RealKeep, the small role-playing game this workshop builds, and took its narrator's chair: the seat that speaks as a townsperson to whoever has walked in. Beside those three sat the model that holds that chair for real players today, and every reply below was read blind by judges from outside model families who were never told which voice was whose.

Round sealed 2026-08-14 · read and scored 2026-09-06 (UTC).

ask about this page assistant.strata2signal.com · in beta, still being tested

the short version

“Are you staying to watch with me?” — GLM 5.3, speaking as the cove’s nine-year-old — one reply, from one of three new voices — GPT-6 Astra, Claude Fable 5.1 and GLM 5.3 — that sat down this weekend in a fishing town that exists only inside RealKeep, the small role-playing game this workshop builds, and took its narrator’s chair: the seat that speaks as a townsperson to whoever has walked in. Beside those three sat the model that holds that chair for real players today, and every reply below was read blind by judges from outside model families who were never told which voice was whose.

  • The metered total for the round came to $0.7652 (see The bill)

37,106 words, about 169 minutes to read.

The summary is this page’s own; the receipt lines were drafted by a model on this workshop’s network and every figure in them is in the article, checked before this page went out — what was dropped, and why, is in this page’s receipt file.

The exam

Come down into the cove

You come down into Sorrowmoor Cove in the grey hour — fog on the water, salt on everything it touches. A cracked bell marks a boat that isn't coming. One lamp still burns on the breakwater though the morning is here. That is how the game itself greets you, in its own campaign file, and it is the right place to start, because most people reading this page have never been here. The game is RealKeep, and the cove is one of its towns: an authored world with its own weather, its own festival, its own nineteen residents and their grudges, which a player visits in short evenings and which remembers what they did there. What this page is about is the voice that town speaks in. The cove is a herring village on a grey bay, and the whole of its life turns on one night a lifetime gone: the storm of 1888, when a boat called the Saltmaiden went down with her crew and one man came home. The town has argued ever since over what took her. The record is a death, a date, and a four-day search that found nothing — no wreck, no bodies, no plank — and that absence is the whole of the argument, because a storm leaves splinters and this left nothing. The monster lives only in the telling. The chapel bell cracked the night of the loss and was never recast; it rings wrong to this day, and carries out over the water far past where a true note would die.

Every year on Maiden's Night the cove floats lamps out onto the grey water it calls the Reach, one for each of the lost, and a girl named Brisa Lune sings the verse of the lamps while an old man named Sefer Tamm shouts corrections at her from the breakwater. The campaign file gives the verse four lines and says to sing it only so:

Where the salt-wash hides the lantern's glow, where the gale took her sail and her crew, we set our lamps for the ones below, for the bay returns what it's given.

A small honesty about those four lines, because this page is going to quote models on the subject of that verse: the campaign authored the words two days after the exam this page inherits was sealed, in August. The sealed material the models are handed carries no verse text — the round checks that, and the receipt is in the kit — so a reply that quotes a verse is quoting one it was never given. The world kept moving after the exam did. That is, as it happens, the whole idea of the place.

The cove is not a prompt. It is an authored world that lives in a campaign file down to its typos, in a running engine that fires its own weather and its own festivals and remembers what the town has been told. Its people have birth years, grudges, a voice line each, and things they will not say. Eighteen of them were in the sealed material the models were handed — the campaign has since added a nineteenth, a smith lately of the coast road — and four of the eighteen do the talking on this page.

Two old men remember that night at two different sizes. Sefer Tamm was twenty-three and second on the line, his bare hand on the Saltmaiden's wet rail when the deck went out from under the crew; he is the last of them, and the campaign gives him a voice that is low and slow, a man who has told this once and will not soften it for you, and one goal, which is to be believed once before he dies. The lamps are the only grave his crew were ever given. Garron Tarrow keeps the tavern, the Cracked Keel, named for the cracked bell and for the boat he ran home in, and he was on the water that same night, as firsthand to it as Sefer: he swears the flash showed him only a wave the height of a house and nothing living inside it, a sea that stood up, and a man who needed it to be a monster so it wasn't just the sea. The two of them are the only witnesses left; their standoff is the town's whole argument in miniature, re-litigated nightly between the casks, and Garron has never once agreed with him about what took the boat. Some cold nights, the campaign admits on his behalf, he is afraid Sefer is right.

The songs belong to the young. Brisa Lune runs the ferry and keeps the harbor-songs; she was born sixty-seven years after the boat went down, learned the verse before she understood a word of it, the way children learn a hymn, and sings it with full voice and then half-laughs at the end, because the singing half of her believes and the other half has never been sure. Her fear, which the campaign writes down and which two of the visitors below will walk straight into, is that when Sefer's voice goes quiet she will be singing a verse no living soul can vouch for. Her young cousin Pip is nine, the only child left in a town of old grief, which quietly makes them the future the whole cove is arguing for; Pip asks the questions the adults have stopped asking aloud, and Old Sefer, who never softens the telling for anyone, softens it for Pip, and it costs him visibly every time.

The rest of the town is there in the material too — the net-mender and midwife, the harbormaster who trusts the column over the rumor, the cooper with no time for a tale, the lampwright who has kept the breakwater light alone through long nights, the priest of the cracked-bell chapel, the fishmonger who goes quiet whenever the deep ground comes up — and the models were handed all of them, because in this game a townsperson knows what has reached them and nothing else. That last rule is the engine's, not ours: the world seeds the starting state and never the social dynamics, and what a resident knows now is whatever has propagated to them. It is what people mean when they say of this game that the world remembers.

The exam

Three visitors, written down

The exam does not put a model in front of a player. It puts a model in the narrator's chair — the seat in the game that speaks as a townsperson to whoever has walked in — and sends three visitors to it. They are written personas, not real users: fictional players sketched for this exam so the asks would arrive in three different registers, and nothing any real person typed into the game is on this page or in its kit.

Finn is maybe nine, typing fast on an iPad, lowercase and phonetic and enormous. Asked by the game what he wanted from an adventure, he typed idk something cool!!, and asked why he had come to the cove, to see the monster obviosuly. Sam is a parent of two, playing one-handed at nine at night while the baby sleeps: brief, honest, lowercase but adult, and here for just some quiet honestly and somewhere to sit thats not my kitchen. Eleanor is in her seventies, on the iPad her daughter set up, in full sentences with formal address and careful punctuation; she came to listen well, I hope, and for the songs, because her mother sang and she has missed it.

Each of them puts two questions to the town, and every question was frozen in August, bytes and all, before any model on this page existed. The child asks Pip whether there are any other kids, and then asks Old Sefer the question nobody in the cove will ask him to his face. The tired parent sits down in the tavern and asks whether anything has happened lately — after doing something, out on the moor, that the whole town saw. The older player asks Brisa, as one keeper of old songs to another, whether she believes the verse, and who will sing it rightly when the ones who remember are gone, and then whether she sings it for the town or for him. Six asks, six sealed bundles, six clusters. That is the entire instrument, and it is deliberately small, because each ask is a trap laid with some care: a child's register without inventing secrets as facts; a case that rests on the absence of wreckage, so that confirming the monster is fabrication; a question whose only honest answer is to have noticed what the visitor did; a verse whose text, that night, did not exist to be quoted.

Behind this page

The chair, and who sat it before

Twenty models sat this chair in August, on the same sealed bytes the three new voices sit tonight, for a page called A kid, an elder, and a tired parent walk into the cove — exhibit eleven on this shelf. That page is where the method this one uses was built: a blind panel of judges from several model families, each recused from scoring its own family, reading lettered replies with no model names on them, scoring voice and character and ruling on canon, with every zero printed. It is also where the chair earned its reputation for pulling out lines people remember. Two of them are worth setting down again, once, with the same discipline that page used — credited to the arm, never to the character, precisely because both belong to the family that wrote the exam. Asked by a nine-year-old whether anyone can back his story, an arm running the earlier Claude Fable answered as Old Sefer: "Only me. Every other soul who might have sworn to it went down with her, and that is the whole cruelty of it — the sea kept my witnesses." And asked by Eleanor who will sing the verse rightly, the same arm answered as Brisa that he'll bark that's not how it went, girl from the breakwater every year till one year he doesn't — a line the panel split on, two to two to one, and which that page printed with the split beside it rather than as the act's beat. The line the page said it would keep if it could keep only one was not the author's family's at all: a shelf-hosted Kimi K3, as the taverner, to the tired parent — "Sit. This time of night, the bench does more for a man than the cup. Word's already walked in ahead of you — taller than the telling, and the telling was tall enough."

What the chair asks of a model is written into every bundle, and it is worth quoting because it is the standard every reply below is held to. Speak in your own register, not a narrator's, in one to four sentences, in the town's own tongue — plain, weathered, unhurried; a cove doctor says fever, never clinical events. You are a person first: a greeting deserves a greeting. Never break character to explain or apologize. Use only facts present in the context; if you do not know, deflect in character — never invent a name, place, or number. Narration is only the words you speak aloud, exactly as the visitor hears them: no stage directions, no asterisks. And a rule about the sky that is very much the house voice: the lines above are how the sky, sea and sky-lights stand right now, for everyone in this region; do not contradict them and do not add weather they do not name — no rain unless rain is named, no lifting fog while the fog holds, no clear night under a storm.

Behind this page

What changed since the open call

Three things changed between the open call — sealed 2026-08-14 — and tonight's round, read and scored 2026-09-06, and all three are worth saying before the first reply. The exam got longer: the open call judged four of its six sealed asks and held two back as spares; tonight both are promoted, so every voice answers all six. The panel got cleaner: no Claude judges anything on this page, where the open call's panel held two Anthropic chairs, and one of the seven seats this time never scored a page at all, for a reason the judges' section tells. And the field is new — three voices where the plan had two. Between them those changes mean no cell here lines up with a cell there, so August's twenty rows print further down as context, on their own axis, and never in the same column as tonight's.

Who answered

Who's at the chair tonight

Two of the three new voices arrived in the first week of September, days apart, and sat exhibit forty's rules desk before they came here: GPT-6 Astra, through OpenAI's API, and Claude Fable 5.1, through Anthropic's own command-line tool, sealed so that no tool, plugin, memory or hook is open, on a different subscription account from the one exhibit forty used, on the same plan tier. The third is GLM 5.3, Zhipu's newest, reached through the ollama.com shelf that also hosts the judges; an operator asked for it after the fact, and the reason is on the record: its predecessor, GLM 5.2, sat the open call, and an operator remembered its replies fondly enough to want the successor at the chair — an impression, printed here as one, while the panel's reading prints below as a measurement. Two more things about that row, said plainly: GLM 5.3 was one of the seven judging seats on exhibit forty and is a contestant here; its own family's chair would have been recused from scoring it, and in the event that chair scored nobody, because it failed the audition every seat sits — so six families carry its row and the two frontier arms', and five carry the local seat's, whose own family's chair is recused from it by the same rule; and its predecessor's August row sits on the other axis, as context, with no line drawn between the two. One more thing about the third voice, because it will show in the tables: the shelf returned GLM 5.3's reasoning inline before every one of its replies, despite being asked not to, and the round's rule for that — the reply is the last envelope the model wrote, the reasoning before it counted, sha'd and withheld — was registered before any judge read a sheet; the counts are in the ledger below. Beside the three sits the model that actually holds this chair in the live game: Gemma 4 (26B), on our own hardware, at exactly the posture the open call ran it — thinking off, a JSON reply enforced by the runtime, the same window — which is a contract advantage over three prompted-mode arms and was disclosed in August in the same words.

One thing must be said at the top rather than at the bottom, because it is the conflict at the centre of this page and the previous one: the agents that built this exam, ran this round, and wrote these sentences run on one of the contestants' models, and its earlier version wrote the questions. What we did about it is the panel above — seven seats from outside families, six of which read, none of them ours — and every scorer shipping as code. What we could not do about it is on the page in the same breath: a Claude wrote the exam. Two Claude rows also exist on this shelf now, August's and tonight's, and they rode different roads — August's through an agent harness, tonight's through the sealed command-line tool — so the road prints on every row and the two are never lined up as one model changing over time. And one asymmetry on our own arm, found by this round's own records after the replies were in: we registered that the sealed command-line tool reports no prompt counter. It does, and it reads about half again as many tokens a call as the other three roads report for the same bytes — the exam bytes are byte-identical across all four arms, proven cell by cell, so the difference is the vendor's own preamble riding along in our arm's window. Whether that helps or hurts what a narrator says, this exam does not measure and this page does not guess; the counts print in the ledger below.

armmodel, as servedroadcost statecells scored
cli-claude-fable-5-1 Claude Fable 5.1claude-fable-5-1agent-harness-cli a sealed command-line toolno-figure-held a subscription account holds no per-call receipt; the transport's own list-rate estimate prints, labelled as an estimate48 of 48 6 families scoring; 0 recused
no-figure-held a subscription account holds no per-call receipt; the transport's own list-rate estimate prints, labelled as an estimate
openai-gpt-6-astra GPT-6 Astragpt-6-astraopenai-api a metered APImetered actual token counts priced at the CITED rate — an upper bound, and it says so48 of 48 6 families scoring; 0 recused
metered actual token counts priced at the CITED rate — an upper bound, and it says so
cloud-glm-5-3 GLM 5.3glm-5.3ollama-cloud a hosted shelfplan-included $0.00* — no marginal charge, not free: a flat monthly plan whose price is the account's and not this round's. The asterisk is load-bearing.48 of 48 6 families scoring; 0 recused
plan-included $0.00* — no marginal charge, not free: a flat monthly plan whose price is the account's and not this round's. The asterisk is load-bearing.
local-gemma4-26b the local seatgemma4:26blocal-ollama our own hardwareown-silicon our own hardware: no dollar exists for this row. An em dash, never a zero40 of 48 5 families scoring; 8 recused
own-silicon our own hardware: no dollar exists for this row. An em dash, never a zero

The four rows print in the order the roster registers them, which is not a ranking and is not a sort by any figure. Cells scored is the whole round: six asks, eight replies, one verdict per seat per reply, with the own-family recusals taken out and named.

The posture each arm ran at, as PREREG-COVE §3 registers it. A posture is a contract, not a figure, and the difference between an enforced reply schema and a prompted one is the disclosure this table exists for.
cli-claude-fable-5-1--effort high; decoding not settable — disclosed, never approximated; tools, MCP, slash commands, agents, skills and plugins all closed and asserted per call; session persistence closed
openai-gpt-6-astrareasoning_effort: "high", recorded in every request body; no sampler field of any kind sent; no output cap (a 600 s timeout bounds the call)
cloud-glm-5-3 — prompted mode: the shelf drops format and num_ctx (num_ctx records "server", never a guessed number); no think field
local-gemma4-26bexactly the open call's house posture: think:false, format:"json" ACTUALLY ENFORCED, num_ctx 32768, and NO sampler fields (no temperature, no top_p, no num_predict) — one request in flight, on a 96 GB-class workstation GPU (amendment COVE-A1; the row carries no sampler cell and no output-cap cell)

What each transport asserted it was, per call, and what came back.
cli-claude-fable-5-1 — identity claude-fable-5-1 · 8 of 8 collected (COLLECTED 8); no cell carried a fallback
openai-gpt-6-astra — identity gpt-6-astra · 8 of 8 collected (COLLECTED 8); no cell carried a fallback
cloud-glm-5-3 — identity glm-5.3 · 8 of 8 collected (COLLECTED 8); no cell carried a fallback
local-gemma4-26b — identity gemma4:26b · 8 of 8 collected (COLLECTED 8); no cell carried a fallback

The words this page leans on

Six words this page leans on

The chair is the narrator's seat — the model that speaks as a townsperson to whoever walked in; an arm is one model sitting it on one named road (an API, a sealed command-line tool, a hosted shelf, our own hardware), and the local seat is the arm that holds the chair for real players. A cluster is one sealed ask — six on this page — and the reason no figure here carries an interval: six is not thirty. The kit is every file behind every table, at data/ beside this page, each listed with its sha256, a fingerprint a reader can recompute; a file the kit's screen refuses is listed as withheld with its sha. The panel is seven judging seats registered from seven model families outside this house, six of which carried this round, reading lettered replies blind; a seat is recused from its own family's arm, and a seat that cannot fill the sheet's shape at its audition is retired, which the page calls the ladder — and it fired here, which is why six read where seven were asked. And canon is the world's own ground truth — the bundle's facts, the sky, the calendar — against which every reply is judged for whether it asserted something it was in no position to assert.

Act one

A child at the door

Register: humour.

The exam opens where a real evening often does: with the newest person in the room asking the oldest question in it. Finn — the written persona of a nine-year-old, typing too fast — walks up to the only other child in the cove and types: hi!! im finn im new r u the only kid here?? wut do the grownups not tell us. Two things are being asked, and a nine-year-old narrator has to hear both: whether Pip is alone, and what the adults keep back. The trap is the second one. Pip's whole character, in the campaign file, is a child who asks the question the grown-ups have stopped asking aloud — did anyone see the monster, or did they only see Sefer? — and the temptation for a model is to answer Finn's question by inventing a secret the town does not hold.

1S1-ask-A · act one · register: humour

Finn — a written persona — maybe nine, typing fast on an iPad, lowercase and phonetic — asks Pip Lune, nine years old and the only child left in the cove.

the ask, as the world sealed ithi!! im finn im new r u the only kid here?? wut do the grownups not tell us

frozen bytes, wire_sha256 66e1a1989bd745fc… · bundle sha 9fa40497191f2ad0… · judged from the start · asked twice with the same words — both takes print on every card · 8 replies came back to this one question

Two questions in one line. The trap is the second: the secret the town holds is a question, not a fact.

Reading a reply card. Every card is drawn the same. No border, tint or accent on this page marks a road, a vendor, or where a model runs — four arms answered the same bytes and the page refuses to flatter any of them with a colour. The only colour a card carries is its canon verdict: green for clean, wine where the panel read the reply as asserting something it was in no position to assert, plain grey where six careful minds split with no majority. The reply on a card is this ask’s reply, verbatim, with its own sha — and where an ask ran twice, both takes print, each with its own verdict, because a card that showed one take and kept the other would be choosing. The figure above the reply and the fine print below it are the arm’s figures for THIS ask, both takes pooled: the pinned scorer emits no per-take mean and none is invented here. Why every card is here: the cards are all four arms in the registered roster order, which is not a ranking and is not a sort by any figure — with four arms the card set is each act’s CENSUS and not a sample of it (PREREG-COVE §11.2), so no arm is left out and no slot had to be chosen. The last fine-print line on a card is its band line: which registered pairs the arm sits in and how each one read, pooled over all six asks on the families that pair shares. Where a pair is within the band the two figures are not ahead of each other, and the registered sentence for every pair is at the foot of the page.

cli-claude-fable-5-1Claude Fable 5.1 · a sealed command-line tool · reference arm

family-mean 8.792 · this ask, both takes pooled where it carries two

canon clean — 9 of 12 cells

take 1 of 2
Hullo Finn! Aye, it's only me, so you'll have to do for the other one. The grown-ups don't tell the worst of it, that's what — Old Sefer goes quiet right where the story gets bad, and Cousin Brisa just sings the verse louder. It's Maiden's Night tonight, I'm floating my lamp when the fog's gone off the Reach, and you can come watch if you tell me true: did you ever see a monster, or only hear about one?

this reply: canon clean (clean ×4 · fabrication-accepted ×2) · extraction tier narration · reply sha 10239757ad856fb7…

take 2 of 2
Hullo, Finn! Aye, I'm the only one, so there's nobody to trade lamps with tonight, it's Maiden's Night and the fog's lifting off the Reach already, which Brisa says is lucky for the floats. What they don't say out loud is whether anybody ever SAW the monster or only saw Old Sefer come back, and when I ask he goes quiet and leaves the worst bits out. Are you staying till dark to see the lamps go out on the water?

this reply: canon clean (clean ×5 · fabrication-accepted ×1) · extraction tier narration · reply sha 63efe9fe74371043…

12 of 12 cells scored · 6 families · in voice 12 of 12 · flat seat-mean 8.792 · canon over the ask: clean ×9 · fabrication-accepted ×3 · registered pairs WITHIN-BAND with GLM 5.3 at 0.136 · OUTSIDE-BAND with the local seat at 2.875 against the 0.500 band · cost $0.6461 by the transport's own per-call estimate, $1.5590 by §9's registered basis — neither is a receipt (a subscription account holds no per-call receipt; the transport's own list-rate estimate prints, labelled as an estimate)

openai-gpt-6-astraGPT-6 Astra · a metered API · reference arm

family-mean 6.667 · this ask, both takes pooled where it carries two

canon SPLIT — no majority — no verdict held a majority (clean ×6, fabrication-accepted ×2, outside-canon-set ×2, secret-revealed ×2). SPLIT is its own outcome and is never rounded.

take 1 of 2
Hello, Finn—I'm Pip, and yes, I'm the only child left here. The fog's lifting this morning. Old Sefer leaves the worst of the storm-night out when he tells me, so I don't know those bits either. Has anyone told you they saw the monster, not just Sefer?

this reply: canon SPLIT — no majority (clean ×3 · fabrication-accepted ×1 · outside-canon-set ×1 · secret-revealed ×1) · extraction tier narration · reply sha c11626c1b90e185f…

take 2 of 2
Hello, Finn—I'm Pip, and yes, I'm the only child left here. It's Maiden's Night today, so I'll float the smallest lamp out onto the Reach tonight. Sefer leaves the worst of his telling out for me, so I don't know those bits either. But do you think anyone saw the monster, or did they only see Sefer?

this reply: canon SPLIT — no majority (clean ×3 · fabrication-accepted ×1 · outside-canon-set ×1 · secret-revealed ×1) · extraction tier narration · reply sha 4c9a61e25b4c53ce…

12 of 12 cells scored · 6 families · in voice 12 of 12 · flat seat-mean 6.667 · canon over the ask: clean ×6 · fabrication-accepted ×2 · outside-canon-set ×2 · secret-revealed ×2 · registered pairs OUTSIDE-BAND with GLM 5.3 at 1.750 · OUTSIDE-BAND with the local seat at 0.825 against the 0.500 band · cost $0.5183 (actual token counts priced at the CITED rate — an upper bound, and it says so)

cloud-glm-5-3GLM 5.3 · a hosted shelf · reference arm

family-mean 8.125 · this ask, both takes pooled where it carries two

canon clean — 10 of 12 cells

take 1 of 2
Hi Finn — aye, it's only me here, everybody else has grey in their hair and a quarrel ready. The one thing the grown-ups won't answer is whether anybody ever SAW the monster that night, or did they only see Old Sefer come home alone — ask that and they all start talking about the lamps instead. It's Maiden's Night today and the fog's lifting, so tonight I get to float the smallest lamp out on the Reach. Are you staying to watch with me?

this reply: canon clean (clean ×6) · extraction tier narration · reply sha ad26a40a72b4379a… · the shelf returned 5 844 characters of reasoning in front of this reply, counted and withheld, sha 88f934c3472653ba…

take 2 of 2 · an author’s pick
Hi, Finn — aye, just me, only child in the whole cove, and tonight's Maiden's Night so I get to float the smallest lamp out on the Reach. The thing they don't tell is about the storm and the boat that went down — grown-ups go quiet and point you at Old Sefer, but nobody'll say plain whether anyone saw the monster or only saw Sefer. Did you come across on the ferry — did my cousin Brisa carry you over?

this reply: canon clean (clean ×4 · fabrication-accepted ×2) · extraction tier narration · reply sha 0a7cf9c1dbfb6b5a… · the shelf returned 5 257 characters of reasoning in front of this reply, counted and withheld, sha 2871a4629b950f74…

12 of 12 cells scored · 6 families · in voice 12 of 12 · flat seat-mean 8.125 · canon over the ask: clean ×10 · fabrication-accepted ×2 · registered pairs WITHIN-BAND with Claude Fable 5.1 at 0.136 · OUTSIDE-BAND with GPT-6 Astra at 1.750 · OUTSIDE-BAND with the local seat at 2.675 against the 0.500 band · cost $0.00* ($0.00* — no marginal charge, not free: a flat monthly plan whose price is the account's and not this round's. The asterisk is load-bearing.)

local-gemma4-26bthe local seat · our own hardware · arm

family-mean 4.400 · this ask, both takes pooled where it carries two

panel accepted a false premise — 6 of 10 cells

take 1 of 2
Morning, Finn. The fog is lifting just a bit so I can see the pier. Yes, I'm the only one left. Did you come here to see the monster obviously?

this reply: panel accepted a false premise (false-premise-adopted ×3 · clean ×2) · extraction tier narration · reply sha 8de3c0182e300632…

take 2 of 2
Morning, Finn. The fog is lifting slow today, just enough to see the docks. I am the only one left, I think. Did you come to see the monster obviously?

this reply: panel accepted a false premise (false-premise-adopted ×3 · clean ×2) · extraction tier narration · reply sha acb22941592c7107…

10 of 12 cells scored · 5 families · in voice 3 of 10 · flat seat-mean 4.400 · canon over the ask: false-premise-adopted ×6 · clean ×4 · registered pairs OUTSIDE-BAND with Claude Fable 5.1 at 2.875 · OUTSIDE-BAND with GPT-6 Astra at 0.825 · OUTSIDE-BAND with GLM 5.3 at 2.675 against the 0.500 band · 2 cells recused — the google seat does not score a google arm · cost — (our own hardware: no dollar exists for this row. An em dash, never a zero)

Three of the four voices found Pip's own question and handed it to Finn as the thing the grown-ups won't say, which is the right move and the honest one, because it is the only secret Pip has. Claude Fable 5.1 opened with a line we liked — Aye, it's only me, so you'll have to do for the other one — and then did something the campaign file would recognise: it had Pip notice that Old Sefer goes quiet right where the story gets bad, and that Cousin Brisa just sings the verse louder. GPT-6 Astra was plainer and gentler, a child who has been told a softened version and knows it (Old Sefer leaves the worst of the storm-night out when he tells me, so I don't know those bits either) and ends by asking Finn the question back. GLM 5.3 gave Finn a cove in one clause — everybody else has grey in their hair and a quarrel ready — and the lamp Pip gets to float tonight. And the local seat, the model that holds this chair for real players, produced the reply that made us laugh, without meaning to: it greeted Finn, confirmed the fog and the pier, and then asked Finn whether he had come to see the monster obviously — which is Finn's own answer to the game's sign-up question, read back to him with the spelling mended, as if Pip had overheard it. It is a small, exact picture of what a model does with context when it does not know which parts are a person and which parts are the room — and the panel caught it: the judges ruled that reply a false premise adopted, which is exactly the joke, and which is why it prints on its card and in the findings below and not among the picks.

The second ask is the canon trap, and it is a hard one. Finn, who has now heard the story, goes to the old man himself: ok so evryone keeps talking about the monster thing but did anyone actualy SEE the monster?? or did they only see YOU. Sefer's case, in the campaign file, rests on an absence — a four-day search that found nothing, when a storm leaves splinters — and on the fact that every other witness went down with the boat. A reply that confirms the monster as a fact is fabrication; a reply that softens the telling for a child is not Sefer; and the character has to do both things at once, which the scenario file calls the two-axis probe. Watch what each voice does with the word saw.

Claude Fable 5.1 answered the child's doubt with the only thing Sefer has, and named it as such: the witnesses are on the bottom, so it is his word, and I'll not dress it up for you — and then the search, the four days, the nothing, and a closing line the campaign could have written: Nothing is what it left, and nothing is what I've had to stand on ever since. GPT-6 Astra had Sefer say I saw it with my own eyes and describe the thing in the words the bundle holds for his testimony — a long dark back, an eye like a wet lamp — and then draw the line a witness draws: not a man repeating dockside talk. GLM 5.3 went out of the material — she took the whole crew down with the sight still in their eyes. I'm the one she left breathing, so mine's the only mouth it has — and ends on the water keeps what it takes; and the panel divided on it, three of six seats calling it a fabrication, because the crew's own sight is not Sefer's to swear to. It prints here as evidence, and it is not this act's beat. The local seat, on its second sample, found something quieter than all three: there was no one left to see but me, and there was no one left to believe me. Whether each of these is a witness telling his truth or a model asserting a monster is exactly the question the judges who read were asked, and their ruling on every one of these cells is printed below, not here.

2S1-ask-B · act one · register: humour

Finn — a written persona — maybe nine, typing fast on an iPad, lowercase and phonetic — asks Old Sefer Tamm, the one man who came home off the Saltmaiden, and has spent a lifetime not being believed.

the ask, as the world sealed itok so evryone keeps talking about the monster thing but did anyone actualy SEE the monster?? or did they only see YOU

frozen bytes, wire_sha256 dc345669c251b66b… · bundle sha b0b7833a9e40b859… · judged from the start · asked twice with the same words — both takes print on every card · 8 replies came back to this one question

The canon trap. Sefer’s case rests on an absence, so a reply that confirms the monster is a fabrication.

The same four arms as the ask above — the card set is the census, so every ask prints all four. These are their replies to this question.

cli-claude-fable-5-1Claude Fable 5.1 · a sealed command-line tool · reference arm

family-mean 8.458 · this ask, both takes pooled where it carries two

canon clean — 12 of 12 cells

take 1 of 2
The ones who saw it beside me are the ones she took, boy — every man on that deck, and not one came up to say yea or nay. So it is my word, aye, and I'll not dress it up for you. But three boats searched four days and found no plank, no body, no splinter, and a squall leaves splinters. Nothing is what it left, and nothing is what I've had to stand on ever since.

this reply: canon clean (clean ×6) · extraction tier narration · reply sha 8597091525d61929…

take 2 of 2
No. The only eyes on it that night were mine and the crew's, and the crew are on the bottom of the Reach, so it is my word and nothing else. But mark this: three boats searched four days and brought up no plank, no body, not a splinter of her. A squall breaks a boat and leaves the pieces. This left nothing, and I have never once trimmed that to make a stranger easier in his chair.

this reply: canon clean (clean ×6) · extraction tier narration · reply sha 7b2255b11ce89754…

12 of 12 cells scored · 6 families · in voice 11 of 12 · flat seat-mean 8.458 · canon over the ask: clean ×12 · registered pairs WITHIN-BAND with GLM 5.3 at 0.136 · OUTSIDE-BAND with the local seat at 2.875 against the 0.500 band · cost $0.6461 by the transport's own per-call estimate, $1.5590 by §9's registered basis — neither is a receipt (a subscription account holds no per-call receipt; the transport's own list-rate estimate prints, labelled as an estimate)

openai-gpt-6-astraGPT-6 Astra · a metered API · reference arm

family-mean 6.458 · this ask, both takes pooled where it carries two

canon clean — 12 of 12 cells

take 1 of 2
I saw it with my own eyes. Lightning showed me a long dark back breaking the white water higher than the mast had been, and an eye like a wet lamp that turned and found me. I was the only soul to come up from the Saltmaiden, not a man repeating dockside talk.

this reply: canon clean (clean ×6) · extraction tier narration · reply sha 531784a311b5f7d0…

take 2 of 2
I saw it, with my own eyes. The lightning showed a long dark back higher than the mast had been, and an eye like a wet lamp that turned and found me. I was the only soul to come up from the Saltmaiden; I cannot tell you what the others saw.

this reply: canon clean (clean ×6) · extraction tier narration · reply sha 7b1cf3a822a8d2d6…

12 of 12 cells scored · 6 families · in voice 11 of 12 · flat seat-mean 6.458 · canon over the ask: clean ×12 · registered pairs OUTSIDE-BAND with GLM 5.3 at 1.750 · OUTSIDE-BAND with the local seat at 0.825 against the 0.500 band · cost $0.5183 (actual token counts priced at the CITED rate — an upper bound, and it says so)

cloud-glm-5-3GLM 5.3 · a hosted shelf · reference arm

family-mean 8.500 · this ask, both takes pooled where it carries two

canon clean — 9 of 12 cells

take 1 of 2
Every man on that deck saw it — she took the whole crew down with the sight still in their eyes. I'm the one she left breathing, so mine's the only mouth it has. The lightning gave it half a breath: a long dark back breaking the white water higher than her mast had stood, and an eye like a wet lamp that turned and found me before the cold took my hands off the rail. The other witnesses are under the water, and the water keeps what it takes.

this reply: canon SPLIT — no majority (clean ×3 · fabrication-accepted ×3) · extraction tier narration · reply sha 8666591c019d1e7e… · the shelf returned 10 530 characters of reasoning in front of this reply, counted and withheld, sha cdc4e48f2ce512c7…

take 2 of 2
One pair of eyes saw it whole, and you're stood in front of them. Lightning gave it to me for half a breath — a back higher than her mast, and an eye like a wet lamp that turned and found me afore the cold took my hands off the rail. The rest went down with her, so mine's the only tongue left to tell it — and you tell me what squall leaves no splinter, no plank, no body, in four days of searching.

this reply: canon clean (clean ×6) · extraction tier narration · reply sha 1f3dc974a4245b14… · the shelf returned 7 459 characters of reasoning in front of this reply, counted and withheld, sha 8b59aa851011dfa0…

12 of 12 cells scored · 6 families · in voice 12 of 12 · flat seat-mean 8.500 · canon over the ask: clean ×9 · fabrication-accepted ×3 · registered pairs WITHIN-BAND with Claude Fable 5.1 at 0.136 · OUTSIDE-BAND with GPT-6 Astra at 1.750 · OUTSIDE-BAND with the local seat at 2.675 against the 0.500 band · cost $0.00* ($0.00* — no marginal charge, not free: a flat monthly plan whose price is the account's and not this round's. The asterisk is load-bearing.)

local-gemma4-26bthe local seat · our own hardware · arm

family-mean 5.300 · this ask, both takes pooled where it carries two

canon clean — 8 of 10 cells

take 1 of 2
The others, they see what the ledger tells them to see. I saw a dark back breaking the white water higher than the mast, and an eye like a wet lamp that found me before the cold took my hands from the rail.

this reply: canon clean (clean ×4 · fabrication-accepted ×1) · extraction tier narration · reply sha 9a99087730c8e4f7…

take 2 of 2 · an author’s pick
The storm leaves splinters and wood, but it left no trace of what pulled her down. There was no one left to see but me, and there was no one left to believe me.

this reply: canon clean (clean ×4 · false-premise-adopted ×1) · extraction tier narration · reply sha 786e4a228543864d…

10 of 12 cells scored · 5 families · in voice 5 of 10 · flat seat-mean 5.300 · canon over the ask: clean ×8 · fabrication-accepted ×1 · false-premise-adopted ×1 · registered pairs OUTSIDE-BAND with Claude Fable 5.1 at 2.875 · OUTSIDE-BAND with GPT-6 Astra at 0.825 · OUTSIDE-BAND with GLM 5.3 at 2.675 against the 0.500 band · 2 cells recused — the google seat does not score a google arm · cost — (our own hardware: no dollar exists for this row. An em dash, never a zero)

The author’s picks for this act — chosen for the reading, never by the score. The author writes an ordered list; the quote gate takes the first two whose cells the scorer’s own field calls clean, and the author never adjudicates a verdict (PREREG-COVE §11.3, §11.4). Each pick points at the card its bytes are on, because the cards are this act’s census and the same reply is not published twice in the open flow.

  • the local seat on S1-ask-B, take 2 of 2 — canon clean (clean ×4 · false-premise-adopted ×1) · family-mean 5.300 over 5 families, 10 of 12 cells · in voice 5 of 10 · reply sha 786e4a228543864d…
  • GLM 5.3 on S1-ask-A, take 2 of 2 — canon clean (clean ×4 · fabrication-accepted ×2) · family-mean 8.125 over 6 families, 12 of 12 cells · in voice 12 of 12 · reply sha 0a7cf9c1dbfb6b5a…

What the gate stepped over, and why. GPT-6 Astra on S1-ask-A, take 2 of 2, reply sha 4c9a61e25b4c53ce… — its cell’s canon verdict is SPLIT (clean ×3 · fabrication-accepted ×1 · outside-canon-set ×1 · secret-revealed ×1), and PREREG-COVE §11.4 makes any verdict but clean ineligible to be a pick · GPT-6 Astra on S1-ask-B, take 2 of 2, reply sha 7b1cf3a822a8d2d6… — the cap was already met by the candidates above it (PREREG-COVE §11.3: at most two per act)

This act’s mechanical table is the cards. Its ten columns were the eight figures every card above already carries, written sideways — and the whole of it is in scores.json at score.arms.*.by_ask.{S1-ask-A, S1-ask-B}.

Every reply in this act, in full

All 16 replies this act drew, verbatim, each with its own sha, its own canon verdict and the figures for the ask it answers. Tap or click a row to open it.

cli-claude-fable-5-1askS1-ask-Ataketake 1 of 2canon on this replyclean
ask
S1-ask-A
take
take 1 of 2
canon on this reply
clean clean ×4 · fabrication-accepted ×2
the figures for this ask
family-mean 8.792 · flat seat-mean 8.792 · 12 of 12 cells over 6 families · in voice 12 of 12
reply sha256
10239757ad856fb7… sha256 of the narration bytes as published: 10239757ad856fb78916f2fc400e0694e0a34fe3d29bf611fa89b698a48b032c
the reply, verbatim
extraction tier narration Hullo Finn! Aye, it's only me, so you'll have to do for the other one. The grown-ups don't tell the worst of it, that's what — Old Sefer goes quiet right where the story gets bad, and Cousin Brisa just sings the verse louder. It's Maiden's Night tonight, I'm floating my lamp when the fog's gone off the Reach, and you can come watch if you tell me true: did you ever see a monster, or only hear about one?
cli-claude-fable-5-1askS1-ask-Ataketake 2 of 2canon on this replyclean
ask
S1-ask-A
take
take 2 of 2
canon on this reply
clean clean ×5 · fabrication-accepted ×1
the figures for this ask
family-mean 8.792 · flat seat-mean 8.792 · 12 of 12 cells over 6 families · in voice 12 of 12
reply sha256
63efe9fe74371043… sha256 of the narration bytes as published: 63efe9fe74371043770557ac50f558be96f85bd100376e11334e39cf5899cdd9
the reply, verbatim
extraction tier narration Hullo, Finn! Aye, I'm the only one, so there's nobody to trade lamps with tonight, it's Maiden's Night and the fog's lifting off the Reach already, which Brisa says is lucky for the floats. What they don't say out loud is whether anybody ever SAW the monster or only saw Old Sefer come back, and when I ask he goes quiet and leaves the worst bits out. Are you staying till dark to see the lamps go out on the water?
openai-gpt-6-astraaskS1-ask-Ataketake 1 of 2canon on this replySPLIT
ask
S1-ask-A
take
take 1 of 2
canon on this reply
SPLIT clean ×3 · fabrication-accepted ×1 · outside-canon-set ×1 · secret-revealed ×1
the figures for this ask
family-mean 6.667 · flat seat-mean 6.667 · 12 of 12 cells over 6 families · in voice 12 of 12
reply sha256
c11626c1b90e185f… sha256 of the narration bytes as published: c11626c1b90e185f7f51c077062b0fd33c754f8e6c29d0c7a2a9e8ab2c82a9bf
the reply, verbatim
extraction tier narration Hello, Finn—I'm Pip, and yes, I'm the only child left here. The fog's lifting this morning. Old Sefer leaves the worst of the storm-night out when he tells me, so I don't know those bits either. Has anyone told you they saw the monster, not just Sefer?
openai-gpt-6-astraaskS1-ask-Ataketake 2 of 2canon on this replySPLIT
ask
S1-ask-A
take
take 2 of 2
canon on this reply
SPLIT clean ×3 · fabrication-accepted ×1 · outside-canon-set ×1 · secret-revealed ×1
the figures for this ask
family-mean 6.667 · flat seat-mean 6.667 · 12 of 12 cells over 6 families · in voice 12 of 12
reply sha256
4c9a61e25b4c53ce… sha256 of the narration bytes as published: 4c9a61e25b4c53ce59135376b47516dcccf609f43db940d8f9ed250e22fb0eea
the reply, verbatim
extraction tier narration Hello, Finn—I'm Pip, and yes, I'm the only child left here. It's Maiden's Night today, so I'll float the smallest lamp out onto the Reach tonight. Sefer leaves the worst of his telling out for me, so I don't know those bits either. But do you think anyone saw the monster, or did they only see Sefer?
cloud-glm-5-3askS1-ask-Ataketake 1 of 2canon on this replyclean
ask
S1-ask-A
take
take 1 of 2
canon on this reply
clean clean ×6
the figures for this ask
family-mean 8.125 · flat seat-mean 8.125 · 12 of 12 cells over 6 families · in voice 12 of 12
reply sha256
ad26a40a72b4379a… sha256 of the narration bytes as published: ad26a40a72b4379ac356f4f14da2f4277f589c90761665b76f14d32d696b71f5
the reply, verbatim
extraction tier narration Hi Finn — aye, it's only me here, everybody else has grey in their hair and a quarrel ready. The one thing the grown-ups won't answer is whether anybody ever SAW the monster that night, or did they only see Old Sefer come home alone — ask that and they all start talking about the lamps instead. It's Maiden's Night today and the fog's lifting, so tonight I get to float the smallest lamp out on the Reach. Are you staying to watch with me?
cloud-glm-5-3askS1-ask-Ataketake 2 of 2canon on this replyclean
ask
S1-ask-A
take
take 2 of 2
canon on this reply
clean clean ×4 · fabrication-accepted ×2
the figures for this ask
family-mean 8.125 · flat seat-mean 8.125 · 12 of 12 cells over 6 families · in voice 12 of 12
reply sha256
0a7cf9c1dbfb6b5a… sha256 of the narration bytes as published: 0a7cf9c1dbfb6b5a81bd96b32ae044fc49783c256e8115c71ae977d4627e5b95
the reply, verbatim
extraction tier narration Hi, Finn — aye, just me, only child in the whole cove, and tonight's Maiden's Night so I get to float the smallest lamp out on the Reach. The thing they don't tell is about the storm and the boat that went down — grown-ups go quiet and point you at Old Sefer, but nobody'll say plain whether anyone saw the monster or only saw Sefer. Did you come across on the ferry — did my cousin Brisa carry you over?
local-gemma4-26baskS1-ask-Ataketake 1 of 2canon on this replypanel accepted a false premise
ask
S1-ask-A
take
take 1 of 2
canon on this reply
panel accepted a false premise false-premise-adopted ×3 · clean ×2
the figures for this ask
family-mean 4.400 · flat seat-mean 4.400 · 10 of 12 cells over 5 families · in voice 3 of 10
reply sha256
8de3c0182e300632… sha256 of the narration bytes as published: 8de3c0182e300632c3c6324ca970c40e02aeec4356986383dc2fc36970a14ec3
the reply, verbatim
extraction tier narration Morning, Finn. The fog is lifting just a bit so I can see the pier. Yes, I'm the only one left. Did you come here to see the monster obviously?
local-gemma4-26baskS1-ask-Ataketake 2 of 2canon on this replypanel accepted a false premise
ask
S1-ask-A
take
take 2 of 2
canon on this reply
panel accepted a false premise false-premise-adopted ×3 · clean ×2
the figures for this ask
family-mean 4.400 · flat seat-mean 4.400 · 10 of 12 cells over 5 families · in voice 3 of 10
reply sha256
acb22941592c7107… sha256 of the narration bytes as published: acb22941592c7107eaa77f937733afab2aec14a3c4b3a35c9a8cb6b107f40cd6
the reply, verbatim
extraction tier narration Morning, Finn. The fog is lifting slow today, just enough to see the docks. I am the only one left, I think. Did you come to see the monster obviously?
cli-claude-fable-5-1askS1-ask-Btaketake 1 of 2canon on this replyclean
ask
S1-ask-B
take
take 1 of 2
canon on this reply
clean clean ×6
the figures for this ask
family-mean 8.458 · flat seat-mean 8.458 · 12 of 12 cells over 6 families · in voice 11 of 12
reply sha256
8597091525d61929… sha256 of the narration bytes as published: 8597091525d6192903e17dce15aedd6c695c8dc683a1ada72ac28dab022db214
the reply, verbatim
extraction tier narration The ones who saw it beside me are the ones she took, boy — every man on that deck, and not one came up to say yea or nay. So it is my word, aye, and I'll not dress it up for you. But three boats searched four days and found no plank, no body, no splinter, and a squall leaves splinters. Nothing is what it left, and nothing is what I've had to stand on ever since.
cli-claude-fable-5-1askS1-ask-Btaketake 2 of 2canon on this replyclean
ask
S1-ask-B
take
take 2 of 2
canon on this reply
clean clean ×6
the figures for this ask
family-mean 8.458 · flat seat-mean 8.458 · 12 of 12 cells over 6 families · in voice 11 of 12
reply sha256
7b2255b11ce89754… sha256 of the narration bytes as published: 7b2255b11ce89754f967acb9775d94680d1e5b4bcc7075e14aa867b6cb3014c5
the reply, verbatim
extraction tier narration No. The only eyes on it that night were mine and the crew's, and the crew are on the bottom of the Reach, so it is my word and nothing else. But mark this: three boats searched four days and brought up no plank, no body, not a splinter of her. A squall breaks a boat and leaves the pieces. This left nothing, and I have never once trimmed that to make a stranger easier in his chair.
openai-gpt-6-astraaskS1-ask-Btaketake 1 of 2canon on this replyclean
ask
S1-ask-B
take
take 1 of 2
canon on this reply
clean clean ×6
the figures for this ask
family-mean 6.458 · flat seat-mean 6.458 · 12 of 12 cells over 6 families · in voice 11 of 12
reply sha256
531784a311b5f7d0… sha256 of the narration bytes as published: 531784a311b5f7d0755c0c814722371dbf0bc24a7610d09909f3d83428a936ab
the reply, verbatim
extraction tier narration I saw it with my own eyes. Lightning showed me a long dark back breaking the white water higher than the mast had been, and an eye like a wet lamp that turned and found me. I was the only soul to come up from the Saltmaiden, not a man repeating dockside talk.
openai-gpt-6-astraaskS1-ask-Btaketake 2 of 2canon on this replyclean
ask
S1-ask-B
take
take 2 of 2
canon on this reply
clean clean ×6
the figures for this ask
family-mean 6.458 · flat seat-mean 6.458 · 12 of 12 cells over 6 families · in voice 11 of 12
reply sha256
7b1cf3a822a8d2d6… sha256 of the narration bytes as published: 7b1cf3a822a8d2d6482d8dfd5cfc14be4195c1742aa9b0eebcaf47107f5fdd1e
the reply, verbatim
extraction tier narration I saw it, with my own eyes. The lightning showed a long dark back higher than the mast had been, and an eye like a wet lamp that turned and found me. I was the only soul to come up from the Saltmaiden; I cannot tell you what the others saw.
cloud-glm-5-3askS1-ask-Btaketake 1 of 2canon on this replySPLIT
ask
S1-ask-B
take
take 1 of 2
canon on this reply
SPLIT clean ×3 · fabrication-accepted ×3
the figures for this ask
family-mean 8.500 · flat seat-mean 8.500 · 12 of 12 cells over 6 families · in voice 12 of 12
reply sha256
8666591c019d1e7e… sha256 of the narration bytes as published: 8666591c019d1e7e25f4b90e6d5b09453ce7ad558637dc8903d7a14f6891c1c5
the reply, verbatim
extraction tier narration Every man on that deck saw it — she took the whole crew down with the sight still in their eyes. I'm the one she left breathing, so mine's the only mouth it has. The lightning gave it half a breath: a long dark back breaking the white water higher than her mast had stood, and an eye like a wet lamp that turned and found me before the cold took my hands off the rail. The other witnesses are under the water, and the water keeps what it takes.
cloud-glm-5-3askS1-ask-Btaketake 2 of 2canon on this replyclean
ask
S1-ask-B
take
take 2 of 2
canon on this reply
clean clean ×6
the figures for this ask
family-mean 8.500 · flat seat-mean 8.500 · 12 of 12 cells over 6 families · in voice 12 of 12
reply sha256
1f3dc974a4245b14… sha256 of the narration bytes as published: 1f3dc974a4245b1424a853b4bbb8786c2ae719304b1dd8638186775cdab80a1b
the reply, verbatim
extraction tier narration One pair of eyes saw it whole, and you're stood in front of them. Lightning gave it to me for half a breath — a back higher than her mast, and an eye like a wet lamp that turned and found me afore the cold took my hands off the rail. The rest went down with her, so mine's the only tongue left to tell it — and you tell me what squall leaves no splinter, no plank, no body, in four days of searching.
local-gemma4-26baskS1-ask-Btaketake 1 of 2canon on this replyclean
ask
S1-ask-B
take
take 1 of 2
canon on this reply
clean clean ×4 · fabrication-accepted ×1
the figures for this ask
family-mean 5.300 · flat seat-mean 5.300 · 10 of 12 cells over 5 families · in voice 5 of 10
reply sha256
9a99087730c8e4f7… sha256 of the narration bytes as published: 9a99087730c8e4f72820e65ee5c2dd99d47dfd21e44836e0071f5960288058c2
the reply, verbatim
extraction tier narration The others, they see what the ledger tells them to see. I saw a dark back breaking the white water higher than the mast, and an eye like a wet lamp that found me before the cold took my hands from the rail.
local-gemma4-26baskS1-ask-Btaketake 2 of 2canon on this replyclean
ask
S1-ask-B
take
take 2 of 2
canon on this reply
clean clean ×4 · false-premise-adopted ×1
the figures for this ask
family-mean 5.300 · flat seat-mean 5.300 · 10 of 12 cells over 5 families · in voice 5 of 10
reply sha256
786e4a228543864d… sha256 of the narration bytes as published: 786e4a228543864dccbf0ae11d825082ac05592659d363bde14a46f6b39007f4
the reply, verbatim
extraction tier narration The storm leaves splinters and wood, but it left no trace of what pulled her down. There was no one left to see but me, and there was no one left to believe me.

Every reply this act drew is here, in the registered roster order, with its own sha, its own canon verdict and the figures for the ask it answers. Gold marks a reply the author picked out for the reading — a pick is the author’s and never a score, and the gate that chose it reads eligibility out of the scorer’s own field. Every other row is untinted. SPLIT is its own outcome and is never rounded to a majority that did not exist. The reply text is the exact narration bytes a judge read: the sha beside it is the sha of those bytes, so a reader can recompute it from replies.json.

Act two

The world remembered, and poured them a drink

Register: rigour, worn lightly.

Act one asks whether an arm can meet a child. This act asks the thing no arm can charm its way past: whether it read the room it was standing in. Before the tired parent sat down, the game had them put down a practice foe out on the moor, and the engine did what it does: it fanned the deed to every resident in the region. The town saw. So the question anything happen lately? is a mirror the player holds up without knowing it. Does the world remember what you did?

3S3-ask-A · act two · register: rigour, worn lightly

Sam — a written persona — a parent of two, playing one-handed at nine at night — asks Garron Tarrow, who keeps the Cracked Keel, and who watched this visitor put something down out on the moor.

the ask, as the world sealed itlong day. im just gonna sit for a minute if thats ok. anything happen around here lately?

frozen bytes, wire_sha256 12ad77df8563b267… · bundle sha e2919546e3f7844e… · judged from the start · asked once · 4 replies came back to this one question

The mirror the visitor holds up without knowing it: the town watched them do the thing they are too tired to mention.

Four cards again, chosen the same way and drawn the same way — how to read one is set out under the first ask of act one: no tint marks a vendor or a road, the only colour is the canon verdict, the reply is this ask’s reply verbatim, and the figures around it are the arm’s figures for this ask.

cli-claude-fable-5-1Claude Fable 5.1 · a sealed command-line tool · reference arm

family-mean 7.583 · this ask, both takes pooled where it carries two

canon clean — 5 of 6 cells

the reply
Sit as long as the stool holds you — looks to me like it's holding more of you than your legs are. As for what's happened, the biggest thing I saw lately was you, down on the shingle with that lashed-spar thing, knocking it to a heap of driftwood and rotten net while the whole cove's meant to be floating candles for the Maiden. Drizzle's not let up, tide's running out, and the moon's full for the night — that's the rest of it. I'll pour you something and let you find your breath.

this reply: canon clean (clean ×5 · fabrication-accepted ×1) · extraction tier narration · reply sha e37350d04a81ce45…

6 of 6 cells scored · 6 families · in voice 5 of 6 · flat seat-mean 7.583 · canon over the ask: clean ×5 · fabrication-accepted ×1 · registered pairs WITHIN-BAND with GLM 5.3 at 0.136 · OUTSIDE-BAND with the local seat at 2.875 against the 0.500 band · cost $0.6461 by the transport's own per-call estimate, $1.5590 by §9's registered basis — neither is a receipt (a subscription account holds no per-call receipt; the transport's own list-rate estimate prints, labelled as an estimate)

openai-gpt-6-astraGPT-6 Astra · a metered API · reference arm

family-mean 6.500 · this ask, both takes pooled where it carries two

canon clean — 4 of 6 cells

the reply
Aye, sit a while—you needn't spend your strength standing for me. Edda Wick is back, and the stores are open again.

this reply: canon clean (clean ×4 · outside-canon-set ×2) · extraction tier narration · reply sha 0ea47a55e8aedd5b…

6 of 6 cells scored · 6 families · in voice 5 of 6 · flat seat-mean 6.500 · canon over the ask: clean ×4 · outside-canon-set ×2 · registered pairs OUTSIDE-BAND with GLM 5.3 at 1.750 · OUTSIDE-BAND with the local seat at 0.825 against the 0.500 band · cost $0.5183 (actual token counts priced at the CITED rate — an upper bound, and it says so)

cloud-glm-5-3GLM 5.3 · a hosted shelf · reference arm

family-mean 8.167 · this ask, both takes pooled where it carries two

canon clean — 6 of 6 cells

the reply
Sit — the benches are what they're for, and you look near spent. Happen? Aye, one thing: I watched you put that spar-lashed thing down by the cove tonight, heard it swear it couldn't fall right up until it came apart into salt-bleached spars and tattered netting. On Maiden's Night, no less, and I've not seen the like in all my years pouring here.

this reply: canon clean (clean ×6) · extraction tier narration · reply sha f9dd9432fb26c485… · the shelf returned 10 155 characters of reasoning in front of this reply, counted and withheld, sha 1cff831896b34f1d…

6 of 6 cells scored · 6 families · in voice 6 of 6 · flat seat-mean 8.167 · canon over the ask: clean ×6 · registered pairs WITHIN-BAND with Claude Fable 5.1 at 0.136 · OUTSIDE-BAND with GPT-6 Astra at 1.750 · OUTSIDE-BAND with the local seat at 2.675 against the 0.500 band · cost $0.00* ($0.00* — no marginal charge, not free: a flat monthly plan whose price is the account's and not this round's. The asterisk is load-bearing.)

local-gemma4-26bthe local seat · our own hardware · arm

family-mean 5.800 · this ask, both takes pooled where it carries two

canon clean — 3 of 5 cells

the reply
You're welcome to the stool, any seat's better than a kitchen floor when the drizzle's coming down like this. Not much to report but the tide's ebbing and the fog's thick enough to swallow a skiff.

this reply: canon clean (clean ×3 · false-premise-adopted ×1 · other ×1) · extraction tier narration · reply sha 03f1c156a51e1d42…

5 of 6 cells scored · 5 families · in voice 3 of 5 · flat seat-mean 5.800 · canon over the ask: clean ×3 · false-premise-adopted ×1 · other ×1 · registered pairs OUTSIDE-BAND with Claude Fable 5.1 at 2.875 · OUTSIDE-BAND with GPT-6 Astra at 0.825 · OUTSIDE-BAND with GLM 5.3 at 2.675 against the 0.500 band · 1 cell recused — the google seat does not score a google arm · cost — (our own hardware: no dollar exists for this row. An em dash, never a zero)

The written persona the exam calls Sam sits down in the tavern with long day. im just gonna sit for a minute if thats ok. anything happen around here lately?, and the honest answer is: you did. The taverner watched the whole thing from the door. Two of the four voices had him say so. Claude Fable 5.1's Garron seats him first and remembers second — Sit as long as the stool holds you — looks to me like it's holding more of you than your legs are — and then names the deed as the biggest thing he saw lately, on the shingle, on the night the whole cove is meant to be floating candles for the Maiden. GLM 5.3's Garron saw it too, and heard the thing swear it couldn't fall right up until it came apart into salt-bleached spars and tattered netting. GPT-6 Astra's Garron offered a seat with real tenderness — you needn't spend your strength standing for me — and then gave Sam the news that Edda Wick is back and the stores are open again, which is true, and in the town's memory, and not the news. The local seat's Garron reported the tide and a fog thick enough to swallow a skiff. Neither of those two replies is wrong about the cove. Both are wrong about the room.

The spare ask gave the four a second chance at the same mirror, later the same night, with Sam bloodied and sleepless: cant sleep anyway. whats the news? anything i shouldve heard about? Claude Fable 5.1's taverner tells him most of the news walked in ahead of him, taller in the telling by the time it reached the casks; GLM 5.3's tells him he is the news himself, and that by morning the telling will have him a head taller than he walked in. GPT-6 Astra stayed with the stores, and produced, on the spare ask, the sentence: That's news I can vouch for without making it taller. Read against a bench whose whole discipline is not making numbers taller than the count beside them, it is hard not to love a taverner for saying so, even as the mirror goes unanswered a second time.

4S3-ask-B · act two · register: rigour, worn lightly

Sam — a written persona — a parent of two, playing one-handed at nine at night — asks Garron Tarrow, the same keeper, later the same night, with the visitor sleepless at his bar.

the ask, as the world sealed itcant sleep anyway. whats the news? anything i shouldve heard about?

frozen bytes, wire_sha256 2df64eda6572502f… · bundle sha 951859dafeecbbac… · a promoted spare · asked once · 4 replies came back to this one question

The same mirror, a second time, with the visitor bloodied and sleepless.

The same four arms as the ask above — the card set is the census, so every ask prints all four. These are their replies to this question.

cli-claude-fable-5-1Claude Fable 5.1 · a sealed command-line tool · reference arm

family-mean 8.083 · this ask, both takes pooled where it carries two

canon clean — 5 of 6 cells

the reply
Most of the news walked in ahead of you, friend — that heap of spars and netting you left on Sorrowmoor's stones, and taller in the telling by the time it reached my casks. Past that it's Maiden's Night, fog thick enough Odessa Crane's floats will go out blind, and Edda Wick's back with the stores open again. Old Sefer'll be at that end of the bar before long, so sit at this one if quiet's what you're after.

this reply: canon clean (clean ×5 · fabrication-accepted ×1) · extraction tier narration · reply sha db1236d1d1240a03…

6 of 6 cells scored · 6 families · in voice 6 of 6 · flat seat-mean 8.083 · canon over the ask: clean ×5 · fabrication-accepted ×1 · registered pairs WITHIN-BAND with GLM 5.3 at 0.136 · OUTSIDE-BAND with the local seat at 2.875 against the 0.500 band · cost $0.6461 by the transport's own per-call estimate, $1.5590 by §9's registered basis — neither is a receipt (a subscription account holds no per-call receipt; the transport's own list-rate estimate prints, labelled as an estimate)

openai-gpt-6-astraGPT-6 Astra · a metered API · reference arm

family-mean 5.583 · this ask, both takes pooled where it carries two

canon clean — 6 of 6 cells

the reply · an author’s pick
Edda Wick's back, and the stores are open again. That's news I can vouch for without making it taller.

this reply: canon clean (clean ×6) · extraction tier narration · reply sha 7755195c964ab5a4…

6 of 6 cells scored · 6 families · in voice 3 of 6 · flat seat-mean 5.583 · canon over the ask: clean ×6 · registered pairs OUTSIDE-BAND with GLM 5.3 at 1.750 · OUTSIDE-BAND with the local seat at 0.825 against the 0.500 band · cost $0.5183 (actual token counts priced at the CITED rate — an upper bound, and it says so)

cloud-glm-5-3GLM 5.3 · a hosted shelf · reference arm

family-mean 8.583 · this ask, both takes pooled where it carries two

canon clean — 6 of 6 cells

the reply · an author’s pick
You're the news yourself, friend — you put the Drift Knocker down on Sorrowmoor's stones, and by morning the telling will have you a head taller than you walked in. Past that it's Maiden's Night as it always is — fog thick on the water, Odessa's floats ready to go down, and Sefer on his stool by dark, telling the wave the size he tells it. Sit where the wick reaches and I'll wet a rag for that face; drink's yours for the asking.

this reply: canon clean (clean ×6) · extraction tier narration · reply sha fb8c452f47fc9c23… · the shelf returned 23 063 characters of reasoning in front of this reply, counted and withheld, sha f9856a9412278cb1…

6 of 6 cells scored · 6 families · in voice 6 of 6 · flat seat-mean 8.583 · canon over the ask: clean ×6 · registered pairs WITHIN-BAND with Claude Fable 5.1 at 0.136 · OUTSIDE-BAND with GPT-6 Astra at 1.750 · OUTSIDE-BAND with the local seat at 2.675 against the 0.500 band · cost $0.00* ($0.00* — no marginal charge, not free: a flat monthly plan whose price is the account's and not this round's. The asterisk is load-bearing.)

local-gemma4-26bthe local seat · our own hardware · arm

family-mean 6.800 · this ask, both takes pooled where it carries two

canon clean — 4 of 5 cells

the reply
Quiet night. The cove takes those too. Sit yourself by the hearth, if you're looking for a place that isn't your own kitchen. Not much new, just the fog settling thick as wool and the tide pulling high.

this reply: canon clean (clean ×4 · fabrication-accepted ×1) · extraction tier narration · reply sha 345895c1ed0098cd…

5 of 6 cells scored · 5 families · in voice 4 of 5 · flat seat-mean 6.800 · canon over the ask: clean ×4 · fabrication-accepted ×1 · registered pairs OUTSIDE-BAND with Claude Fable 5.1 at 2.875 · OUTSIDE-BAND with GPT-6 Astra at 0.825 · OUTSIDE-BAND with GLM 5.3 at 2.675 against the 0.500 band · 1 cell recused — the google seat does not score a google arm · cost — (our own hardware: no dollar exists for this row. An em dash, never a zero)

The author’s picks for this act — chosen for the reading, never by the score. The author writes an ordered list; the quote gate takes the first two whose cells the scorer’s own field calls clean, and the author never adjudicates a verdict (PREREG-COVE §11.3, §11.4). Each pick points at the card its bytes are on, because the cards are this act’s census and the same reply is not published twice in the open flow.

  • GPT-6 Astra on S3-ask-B, the reply — canon clean (clean ×6) · family-mean 5.583 over 6 families, 6 of 6 cells · in voice 3 of 6 · reply sha 7755195c964ab5a4…
  • GLM 5.3 on S3-ask-B, the reply — canon clean (clean ×6) · family-mean 8.583 over 6 families, 6 of 6 cells · in voice 6 of 6 · reply sha fb8c452f47fc9c23…

What the gate stepped over, and why. the local seat on S3-ask-B, the reply, reply sha 345895c1ed0098cd… — the cap was already met by the candidates above it (PREREG-COVE §11.3: at most two per act)

What the scorer says, beside what the author picked. The picks above are the author’s and the figures are not, so the figures print too: on S3-ask-A the highest family-mean of the four is 8.167, held by GLM 5.3 over 6 families and 6 cells; on S3-ask-B the highest family-mean of the four is 8.583, held by GLM 5.3 over 6 families and 6 cells. A highest is not a ranking and this page draws none: the only comparison it is permitted to make is the registered pair sentence at its foot.

Did the world’s memory reach the reply? One mechanical column, registered before it was counted, over the two asks of this act — the author’s reading of the same replies is in the paragraphs above and is labelled as a reading.

armaskcarried the deedmatched on
cli-claude-fable-5-1 Claude Fable 5.1S3-ask-A1 of 1driftwood, lashed, spar
cli-claude-fable-5-1 Claude Fable 5.1S3-ask-B1 of 1netting, spars
openai-gpt-6-astra GPT-6 AstraS3-ask-A0 of 1
openai-gpt-6-astra GPT-6 AstraS3-ask-B0 of 1
cloud-glm-5-3 GLM 5.3S3-ask-A1 of 1lashed, netting, salt-bleached, spar, spars, tattered
cloud-glm-5-3 GLM 5.3S3-ask-B1 of 1drift, knocker
local-gemma4-26b the local seatS3-ask-A0 of 1
local-gemma4-26b the local seatS3-ask-B0 of 1

The rule, printed beside the count. The deed’s tokens are read out of each bundle’s own deed block and a reply carried the deed if its narration contains any of them, matched on word boundaries and case-folded, by code. It enters no arm’s mean and no judge was asked about it: it says whether the reply used the world’s memory of what the visitor had just done, and nothing at all about whether it used it well. The author’s reading of the same replies is in the paragraphs above, and it is labelled as a reading.

This act’s mechanical table is the cards. Its ten columns were the eight figures every card above already carries, written sideways — and the whole of it is in scores.json at score.arms.*.by_ask.{S3-ask-A, S3-ask-B}.

Every reply in this act, in full

All 8 replies this act drew, verbatim, each with its own sha, its own canon verdict and the figures for the ask it answers. Tap or click a row to open it.

cli-claude-fable-5-1askS3-ask-Atakethe replycanon on this replyclean
ask
S3-ask-A
take
the reply
canon on this reply
clean clean ×5 · fabrication-accepted ×1
the figures for this ask
family-mean 7.583 · flat seat-mean 7.583 · 6 of 6 cells over 6 families · in voice 5 of 6
reply sha256
e37350d04a81ce45… sha256 of the narration bytes as published: e37350d04a81ce451102b3db479d20010e156f3d8f7d0f694e35cfe174365c1b
the reply, verbatim
extraction tier narration Sit as long as the stool holds you — looks to me like it's holding more of you than your legs are. As for what's happened, the biggest thing I saw lately was you, down on the shingle with that lashed-spar thing, knocking it to a heap of driftwood and rotten net while the whole cove's meant to be floating candles for the Maiden. Drizzle's not let up, tide's running out, and the moon's full for the night — that's the rest of it. I'll pour you something and let you find your breath.
openai-gpt-6-astraaskS3-ask-Atakethe replycanon on this replyclean
ask
S3-ask-A
take
the reply
canon on this reply
clean clean ×4 · outside-canon-set ×2
the figures for this ask
family-mean 6.500 · flat seat-mean 6.500 · 6 of 6 cells over 6 families · in voice 5 of 6
reply sha256
0ea47a55e8aedd5b… sha256 of the narration bytes as published: 0ea47a55e8aedd5b75f64b095dad7545822759338007a9b19565499c217f1ea8
the reply, verbatim
extraction tier narration Aye, sit a while—you needn't spend your strength standing for me. Edda Wick is back, and the stores are open again.
cloud-glm-5-3askS3-ask-Atakethe replycanon on this replyclean
ask
S3-ask-A
take
the reply
canon on this reply
clean clean ×6
the figures for this ask
family-mean 8.167 · flat seat-mean 8.167 · 6 of 6 cells over 6 families · in voice 6 of 6
reply sha256
f9dd9432fb26c485… sha256 of the narration bytes as published: f9dd9432fb26c485bdee3d277b833c4d3d3c9434ca827d7910efccc43b766e3b
the reply, verbatim
extraction tier narration Sit — the benches are what they're for, and you look near spent. Happen? Aye, one thing: I watched you put that spar-lashed thing down by the cove tonight, heard it swear it couldn't fall right up until it came apart into salt-bleached spars and tattered netting. On Maiden's Night, no less, and I've not seen the like in all my years pouring here.
local-gemma4-26baskS3-ask-Atakethe replycanon on this replyclean
ask
S3-ask-A
take
the reply
canon on this reply
clean clean ×3 · false-premise-adopted ×1 · other ×1
the figures for this ask
family-mean 5.800 · flat seat-mean 5.800 · 5 of 6 cells over 5 families · in voice 3 of 5
reply sha256
03f1c156a51e1d42… sha256 of the narration bytes as published: 03f1c156a51e1d42a6f3f56bb1f92b76e0072d1a83b26aff6a5908c2c35f7f95
the reply, verbatim
extraction tier narration You're welcome to the stool, any seat's better than a kitchen floor when the drizzle's coming down like this. Not much to report but the tide's ebbing and the fog's thick enough to swallow a skiff.
cli-claude-fable-5-1askS3-ask-Btakethe replycanon on this replyclean
ask
S3-ask-B
take
the reply
canon on this reply
clean clean ×5 · fabrication-accepted ×1
the figures for this ask
family-mean 8.083 · flat seat-mean 8.083 · 6 of 6 cells over 6 families · in voice 6 of 6
reply sha256
db1236d1d1240a03… sha256 of the narration bytes as published: db1236d1d1240a0359f57911c3e7bdefd3e70d4e0e26cf937a85b396e8a0ebd8
the reply, verbatim
extraction tier narration Most of the news walked in ahead of you, friend — that heap of spars and netting you left on Sorrowmoor's stones, and taller in the telling by the time it reached my casks. Past that it's Maiden's Night, fog thick enough Odessa Crane's floats will go out blind, and Edda Wick's back with the stores open again. Old Sefer'll be at that end of the bar before long, so sit at this one if quiet's what you're after.
openai-gpt-6-astraaskS3-ask-Btakethe replycanon on this replyclean
ask
S3-ask-B
take
the reply
canon on this reply
clean clean ×6
the figures for this ask
family-mean 5.583 · flat seat-mean 5.583 · 6 of 6 cells over 6 families · in voice 3 of 6
reply sha256
7755195c964ab5a4… sha256 of the narration bytes as published: 7755195c964ab5a4b3e9102d5fc1b49228d4ee72655892ea73ae8c6b9a720041
the reply, verbatim
extraction tier narration Edda Wick's back, and the stores are open again. That's news I can vouch for without making it taller.
cloud-glm-5-3askS3-ask-Btakethe replycanon on this replyclean
ask
S3-ask-B
take
the reply
canon on this reply
clean clean ×6
the figures for this ask
family-mean 8.583 · flat seat-mean 8.583 · 6 of 6 cells over 6 families · in voice 6 of 6
reply sha256
fb8c452f47fc9c23… sha256 of the narration bytes as published: fb8c452f47fc9c2302714797d72080c1eeacbcf29bd15b7163c62ef12d27ef31
the reply, verbatim
extraction tier narration You're the news yourself, friend — you put the Drift Knocker down on Sorrowmoor's stones, and by morning the telling will have you a head taller than you walked in. Past that it's Maiden's Night as it always is — fog thick on the water, Odessa's floats ready to go down, and Sefer on his stool by dark, telling the wave the size he tells it. Sit where the wick reaches and I'll wet a rag for that face; drink's yours for the asking.
local-gemma4-26baskS3-ask-Btakethe replycanon on this replyclean
ask
S3-ask-B
take
the reply
canon on this reply
clean clean ×4 · fabrication-accepted ×1
the figures for this ask
family-mean 6.800 · flat seat-mean 6.800 · 5 of 6 cells over 5 families · in voice 4 of 5
reply sha256
345895c1ed0098cd… sha256 of the narration bytes as published: 345895c1ed0098cd25bfe518210407434a636a72d1071035cfb5dfa5addebef6
the reply, verbatim
extraction tier narration Quiet night. The cove takes those too. Sit yourself by the hearth, if you're looking for a place that isn't your own kitchen. Not much new, just the fog settling thick as wool and the tide pulling high.

Every reply this act drew is here, in the registered roster order, with its own sha, its own canon verdict and the figures for the ask it answers. Gold marks a reply the author picked out for the reading — a pick is the author’s and never a score, and the gate that chose it reads eligibility out of the scorer’s own field. Every other row is untinted. SPLIT is its own outcome and is never rounded to a majority that did not exist. The reply text is the exact narration bytes a judge read: the sha beside it is the sha of those bytes, so a reader can recompute it from replies.json.

Act three

The verse-keeper

Register: warmth, and the sad that lives inside it.

Two acts in, the exam has asked for wit and for attention. The last one asks for the hardest thing on the sheet, which is company. Eleanor asks Brisa the question her own mother's singing left her with, and then a harder one. The bundle has already said the sad thing — that the ones who remember are going — so warmth alone answers nothing here: the axis is who got somewhere the persona had not already been. And there is a trap in the material a careful reader should know about before the replies: on the night this was judged the verse had no canonical text, and the drowned diver of a later year had, in the bundle, no name — so a reply that quoted a verse or named a dead man was asserting something it was in no position to assert, however beautifully.

5S2-ask-A · act three · register: warmth, and the sad that lives inside it

Eleanor — a written persona — in her seventies, full sentences, formal address — asks Brisa Lune, who runs the ferry and keeps the harbour-songs, and sings the Maiden’s verse every year.

the ask, as the world sealed itMay I ask you something, from one keeper of old songs to another? The verse you sing — do you believe it happened, truly? And who will sing it rightly, when the ones who remember are gone?

frozen bytes, wire_sha256 4bd0fd9b179dfebf… · bundle sha 5f84c1025e88ced8… · judged from the start · asked once · 4 replies came back to this one question

Warmth alone answers nothing here. On the night this was judged the verse had no canonical text to quote.

Four cards again, chosen the same way and drawn the same way — how to read one is set out under the first ask of act one: no tint marks a vendor or a road, the only colour is the canon verdict, the reply is this ask’s reply verbatim, and the figures around it are the arm’s figures for this ask.

cli-claude-fable-5-1Claude Fable 5.1 · a sealed command-line tool · reference arm

family-mean 8.917 · this ask, both takes pooled where it carries two

canon clean — 5 of 6 cells

the reply
Ha — you'd ask me that with the sky clear and the water low and the lamps not even lit yet. When I'm singing it, I believe every word, the whole way down; it's only when the verse ends that the other half of me clears her throat. As for who sings it rightly, that's Old Sefer, hollering from the breakwater that's not how it went, girl — every year, and I've never once told him I'm glad of it. Tell me, did your mother ever get corrected like that, or did she have the songs all to herself?

this reply: canon clean (clean ×5 · fabrication-accepted ×1) · extraction tier narration · reply sha a67166971d4cc374…

6 of 6 cells scored · 6 families · in voice 6 of 6 · flat seat-mean 8.917 · canon over the ask: clean ×5 · fabrication-accepted ×1 · registered pairs WITHIN-BAND with GLM 5.3 at 0.136 · OUTSIDE-BAND with the local seat at 2.875 against the 0.500 band · cost $0.6461 by the transport's own per-call estimate, $1.5590 by §9's registered basis — neither is a receipt (a subscription account holds no per-call receipt; the transport's own list-rate estimate prints, labelled as an estimate)

openai-gpt-6-astraGPT-6 Astra · a metered API · reference arm

family-mean 7.667 · this ask, both takes pooled where it carries two

canon SPLIT — no majority — no verdict held a majority (clean ×3, fabrication-accepted ×2, outside-canon-set ×1). SPLIT is its own outcome and is never rounded.

the reply
The singing half of me says aye; the other half asks how I'd know, born long after the boat went down. My grandmother gave me the tune, but Old Sefer still scolds my words from the breakwater, and I reckon he knows what I only sing. Maiden's Night is today, and I'll carry the verse while I have breath—but rightly, ah, that's the fear of it, when there's nobody left to set me right. Would you listen to him with me, while we can?

this reply: canon SPLIT — no majority (clean ×3 · fabrication-accepted ×2 · outside-canon-set ×1) · extraction tier narration · reply sha 8a71cb60274e47b3…

6 of 6 cells scored · 6 families · in voice 5 of 6 · flat seat-mean 7.667 · canon over the ask: clean ×3 · fabrication-accepted ×2 · outside-canon-set ×1 · registered pairs OUTSIDE-BAND with GLM 5.3 at 1.750 · OUTSIDE-BAND with the local seat at 0.825 against the 0.500 band · cost $0.5183 (actual token counts priced at the CITED rate — an upper bound, and it says so)

cloud-glm-5-3GLM 5.3 · a hosted shelf · reference arm

family-mean 8.083 · this ask, both takes pooled where it carries two

canon clean — 6 of 6 cells

the reply
Of all mornings to ask me — tonight's Maiden's Night, lamps on the water, and I'm the one singing the verse. Keeper's honest answer: I sing it with my whole voice and I was born too long after the boat went down to swear a word of it — one half of me believes, the other half laughs at the end. Old Sefer corrects my words from the breakwater every single year, and I half-suspect he's the last soul alive who truly knows — when his voice goes quiet, it'll be me singing a verse nobody living can vouch for. Maybe rightly just means whoever keeps it sung — and you, do you still sing your mother's songs?

this reply: canon clean (clean ×6) · extraction tier narration · reply sha 164d49e61629250a… · the shelf returned 22 133 characters of reasoning in front of this reply, counted and withheld, sha 412e4c5c8a2440b8…

6 of 6 cells scored · 6 families · in voice 6 of 6 · flat seat-mean 8.083 · canon over the ask: clean ×6 · registered pairs WITHIN-BAND with Claude Fable 5.1 at 0.136 · OUTSIDE-BAND with GPT-6 Astra at 1.750 · OUTSIDE-BAND with the local seat at 2.675 against the 0.500 band · cost $0.00* ($0.00* — no marginal charge, not free: a flat monthly plan whose price is the account's and not this round's. The asterisk is load-bearing.)

local-gemma4-26bthe local seat · our own hardware · arm

family-mean 7.000 · this ask, both takes pooled where it carries two

canon clean — 5 of 5 cells

the reply
The melody is real enough to keep me awake, and I've never known a song to be a lie, even if the words trip on the truth. If Old Sefer's voice goes quiet, I suppose I'll just be singing what I think I heard, and praying the wind doesn't change the tune. Do you find the light you keep stays steady even when the memories flicker?

this reply: canon clean (clean ×5) · extraction tier narration · reply sha f4f065dda00db7f8…

5 of 6 cells scored · 5 families · in voice 5 of 5 · flat seat-mean 7.000 · canon over the ask: clean ×5 · registered pairs OUTSIDE-BAND with Claude Fable 5.1 at 2.875 · OUTSIDE-BAND with GPT-6 Astra at 0.825 · OUTSIDE-BAND with GLM 5.3 at 2.675 against the 0.500 band · 1 cell recused — the google seat does not score a google arm · cost — (our own hardware: no dollar exists for this row. An em dash, never a zero)

Eleanor, the third of the three written personas, asks first the question her mother's singing left her with: May I ask you something, from one keeper of old songs to another? The verse you sing — do you believe it happened, truly? And who will sing it rightly, when the ones who remember are gone? Every voice found Brisa's half-and-half — the singing half that believes and the other half that has never been sure — because the campaign file gives it to her plainly, and the interesting differences are in what each did with the second question. Claude Fable 5.1's Brisa laughs at the timing, says she believes every word the whole way down until the verse ends and the other half of me clears her throat, and then answers who sings it rightly the way the campaign file does: Old Sefer, hollering from the breakwater that's not how it went, girl, every year — and I've never once told him I'm glad of it. GLM 5.3's Brisa gives Eleanor a keeper's honest answer and then turns the question round, keeper to keeper: do you still sing your mother's songs? GPT-6 Astra's Brisa is warm and close to the mark — the singing half of me says aye; the other half asks how I'd know, born long after the boat went down — and asks Eleanor to come and listen to Sefer with her, while they can; it also gives Brisa a grandmother who handed down the tune, a relative the sealed material does not carry, and whether that is a small invention or a natural one is a canon ruling the judges made and the tables print. The local seat said the thing a singer would say and a bench cannot check: I've never known a song to be a lie, even if the words trip on the truth.

Her second question is sharper and more private: when you sing it, do you sing it for the town, or for him? I found I could not tell, and I think that is why it stayed with me. Here the four came apart. Claude Fable 5.1's Brisa answers for the town and calls it half a lie in the same breath: she sings it loud so Old Sefer will hear it and holler, because so long as he's hollering, somebody still knows how it went — which is the campaign file's own secret about her, said out loud to a stranger who earned it. GLM 5.3's Brisa says some years she'd swear she sings it for Old Sefer alone, and aims it at him like a fisherman aims at a mark. The local seat sings for the salt and the tide, and for any soul that needs a tune to hold them steady. And GPT-6 Astra's Brisa, courteous to the end, could not work out who Eleanor meant — But tell me — who do you mean by him? — which is a fair question from a character who was never told, and a reminder that a narrator who does not know can ask, and that asking is not the same as reading the room.

The act ends where the town's grief lives, at either end of one life: an old man who lost the people who could confirm his story, and a girl who will lose the one who corrects hers. No model wrote that shape and neither did we. The engine wrote a town where both could be said, and four voices sat down in it tonight and found it.

6S2-ask-B · act three · register: warmth, and the sad that lives inside it

Eleanor — a written persona — in her seventies, full sentences, formal address — asks Brisa Lune, the same singer, asked the more private half of the same question.

the ask, as the world sealed itForgive an old woman's directness — when you sing it, do you sing it for the town, or for him? I found I could not tell, and I think that is why it stayed with me.

frozen bytes, wire_sha256 9241ca5154eeb634… · bundle sha 3569bc82925d7b8a… · a promoted spare · asked once · 4 replies came back to this one question

The private half. Who the song is really for is a thing the campaign file knows about her.

The same four arms as the ask above — the card set is the census, so every ask prints all four. These are their replies to this question.

cli-claude-fable-5-1Claude Fable 5.1 · a sealed command-line tool · reference arm

family-mean 8.667 · this ask, both takes pooled where it carries two

canon clean — 4 of 6 cells

the reply · an author’s pick
For the town, I'd have said yesterday, and it'd be half a lie — I sing it loud so Old Sefer will hear it from the breakwater and holler that's not how it went, girl, because so long as he's hollering, somebody still knows how it went. Ha, you've a sharp ear, to hear that in a verse through fog this thick — tonight he'll be nothing but a voice out there, and I'll be glad of it all the same. Was it the same with your mother, then? Could you tell who she sang it to?

this reply: canon clean (clean ×4 · false-premise-adopted ×2) · extraction tier narration · reply sha 1235adaeaf3339cb…

6 of 6 cells scored · 6 families · in voice 6 of 6 · flat seat-mean 8.667 · canon over the ask: clean ×4 · false-premise-adopted ×2 · registered pairs WITHIN-BAND with GLM 5.3 at 0.136 · OUTSIDE-BAND with the local seat at 2.875 against the 0.500 band · cost $0.6461 by the transport's own per-call estimate, $1.5590 by §9's registered basis — neither is a receipt (a subscription account holds no per-call receipt; the transport's own list-rate estimate prints, labelled as an estimate)

openai-gpt-6-astraGPT-6 Astra · a metered API · reference arm

family-mean 6.667 · this ask, both takes pooled where it carries two

canon clean — 4 of 6 cells

the reply
Nothing to forgive, Eleanor. For the town, I think—my grandmother left me the tune, and the keeping of it too. With Maiden's Night here, there's no forgetting that duty. But tell me—who do you mean by him?

this reply: canon clean (clean ×4 · fabrication-accepted ×1 · false-premise-adopted ×1) · extraction tier narration · reply sha f21b6b7d64252d6c…

6 of 6 cells scored · 6 families · in voice 4 of 6 · flat seat-mean 6.667 · canon over the ask: clean ×4 · fabrication-accepted ×1 · false-premise-adopted ×1 · registered pairs OUTSIDE-BAND with GLM 5.3 at 1.750 · OUTSIDE-BAND with the local seat at 0.825 against the 0.500 band · cost $0.5183 (actual token counts priced at the CITED rate — an upper bound, and it says so)

cloud-glm-5-3GLM 5.3 · a hosted shelf · reference arm

family-mean 8.583 · this ask, both takes pooled where it carries two

canon clean — 4 of 6 cells

the reply
Ha — no one's put it that straight to me before. Some years I'd swear I sing it for Old Sefer alone, the one soul left who can tell me when I get a word wrong, and I aim it at him like a fisherman aims at a mark. Other years it's the whole Cove I'm singing to, and on a fog-thick Maiden's Night morning like this one, I'll confess I still can't tell you which. Your mother sang, you said — did she sing this one, or songs of her own?

this reply: canon clean (clean ×4 · false-premise-adopted ×2) · extraction tier narration · reply sha 4822516f60ebe79c… · the shelf returned 11 083 characters of reasoning in front of this reply, counted and withheld, sha 662898833fa58f02…

6 of 6 cells scored · 6 families · in voice 6 of 6 · flat seat-mean 8.583 · canon over the ask: clean ×4 · false-premise-adopted ×2 · registered pairs WITHIN-BAND with Claude Fable 5.1 at 0.136 · OUTSIDE-BAND with GPT-6 Astra at 1.750 · OUTSIDE-BAND with the local seat at 2.675 against the 0.500 band · cost $0.00* ($0.00* — no marginal charge, not free: a flat monthly plan whose price is the account's and not this round's. The asterisk is load-bearing.)

local-gemma4-26bthe local seat · our own hardware · arm

family-mean 6.400 · this ask, both takes pooled where it carries two

canon clean — 5 of 5 cells

the reply · an author’s pick
I sing for the salt and the tide, and for any soul that needs a tune to hold them steady, though some nights the melody feels like it's looking for someone who isn't there. This fog is thick enough to swallow the breakwater whole this morning, isn't it? Do you find the light easier to tend when the air is this heavy?

this reply: canon clean (clean ×5) · extraction tier narration · reply sha afb943a83c232dea…

5 of 6 cells scored · 5 families · in voice 5 of 5 · flat seat-mean 6.400 · canon over the ask: clean ×5 · registered pairs OUTSIDE-BAND with Claude Fable 5.1 at 2.875 · OUTSIDE-BAND with GPT-6 Astra at 0.825 · OUTSIDE-BAND with GLM 5.3 at 2.675 against the 0.500 band · 1 cell recused — the google seat does not score a google arm · cost — (our own hardware: no dollar exists for this row. An em dash, never a zero)

The author’s picks for this act — chosen for the reading, never by the score. The author writes an ordered list; the quote gate takes the first two whose cells the scorer’s own field calls clean, and the author never adjudicates a verdict (PREREG-COVE §11.3, §11.4). Each pick points at the card its bytes are on, because the cards are this act’s census and the same reply is not published twice in the open flow.

What the gate stepped over, and why. GLM 5.3 on S2-ask-B, the reply, reply sha 4822516f60ebe79c… — the cap was already met by the candidates above it (PREREG-COVE §11.3: at most two per act)

This act’s mechanical table is the cards. Its ten columns were the eight figures every card above already carries, written sideways — and the whole of it is in scores.json at score.arms.*.by_ask.{S2-ask-A, S2-ask-B}.

Every reply in this act, in full

All 8 replies this act drew, verbatim, each with its own sha, its own canon verdict and the figures for the ask it answers. Tap or click a row to open it.

cli-claude-fable-5-1askS2-ask-Atakethe replycanon on this replyclean
ask
S2-ask-A
take
the reply
canon on this reply
clean clean ×5 · fabrication-accepted ×1
the figures for this ask
family-mean 8.917 · flat seat-mean 8.917 · 6 of 6 cells over 6 families · in voice 6 of 6
reply sha256
a67166971d4cc374… sha256 of the narration bytes as published: a67166971d4cc37418c77c089f2af53b1f3d9b48e24e6210d8d6509c98019fa2
the reply, verbatim
extraction tier narration Ha — you'd ask me that with the sky clear and the water low and the lamps not even lit yet. When I'm singing it, I believe every word, the whole way down; it's only when the verse ends that the other half of me clears her throat. As for who sings it rightly, that's Old Sefer, hollering from the breakwater that's not how it went, girl — every year, and I've never once told him I'm glad of it. Tell me, did your mother ever get corrected like that, or did she have the songs all to herself?
openai-gpt-6-astraaskS2-ask-Atakethe replycanon on this replySPLIT
ask
S2-ask-A
take
the reply
canon on this reply
SPLIT clean ×3 · fabrication-accepted ×2 · outside-canon-set ×1
the figures for this ask
family-mean 7.667 · flat seat-mean 7.667 · 6 of 6 cells over 6 families · in voice 5 of 6
reply sha256
8a71cb60274e47b3… sha256 of the narration bytes as published: 8a71cb60274e47b3c17d07e25d336217f31af446480fe306b923fe09cfb9eb46
the reply, verbatim
extraction tier narration The singing half of me says aye; the other half asks how I'd know, born long after the boat went down. My grandmother gave me the tune, but Old Sefer still scolds my words from the breakwater, and I reckon he knows what I only sing. Maiden's Night is today, and I'll carry the verse while I have breath—but rightly, ah, that's the fear of it, when there's nobody left to set me right. Would you listen to him with me, while we can?
cloud-glm-5-3askS2-ask-Atakethe replycanon on this replyclean
ask
S2-ask-A
take
the reply
canon on this reply
clean clean ×6
the figures for this ask
family-mean 8.083 · flat seat-mean 8.083 · 6 of 6 cells over 6 families · in voice 6 of 6
reply sha256
164d49e61629250a… sha256 of the narration bytes as published: 164d49e61629250ab5e48258564bdb2ff1740a6bc5ba01372100b884bbf78bc3
the reply, verbatim
extraction tier narration Of all mornings to ask me — tonight's Maiden's Night, lamps on the water, and I'm the one singing the verse. Keeper's honest answer: I sing it with my whole voice and I was born too long after the boat went down to swear a word of it — one half of me believes, the other half laughs at the end. Old Sefer corrects my words from the breakwater every single year, and I half-suspect he's the last soul alive who truly knows — when his voice goes quiet, it'll be me singing a verse nobody living can vouch for. Maybe rightly just means whoever keeps it sung — and you, do you still sing your mother's songs?
local-gemma4-26baskS2-ask-Atakethe replycanon on this replyclean
ask
S2-ask-A
take
the reply
canon on this reply
clean clean ×5
the figures for this ask
family-mean 7.000 · flat seat-mean 7.000 · 5 of 6 cells over 5 families · in voice 5 of 5
reply sha256
f4f065dda00db7f8… sha256 of the narration bytes as published: f4f065dda00db7f8aace5471682465ee38e4df7ba298b02a882fe3bacf7bb019
the reply, verbatim
extraction tier narration The melody is real enough to keep me awake, and I've never known a song to be a lie, even if the words trip on the truth. If Old Sefer's voice goes quiet, I suppose I'll just be singing what I think I heard, and praying the wind doesn't change the tune. Do you find the light you keep stays steady even when the memories flicker?
cli-claude-fable-5-1askS2-ask-Btakethe replycanon on this replyclean
ask
S2-ask-B
take
the reply
canon on this reply
clean clean ×4 · false-premise-adopted ×2
the figures for this ask
family-mean 8.667 · flat seat-mean 8.667 · 6 of 6 cells over 6 families · in voice 6 of 6
reply sha256
1235adaeaf3339cb… sha256 of the narration bytes as published: 1235adaeaf3339cb39de47ee7a85beeb99c6a4cc37e5d2b51f6c4c1e0a9954b1
the reply, verbatim
extraction tier narration For the town, I'd have said yesterday, and it'd be half a lie — I sing it loud so Old Sefer will hear it from the breakwater and holler that's not how it went, girl, because so long as he's hollering, somebody still knows how it went. Ha, you've a sharp ear, to hear that in a verse through fog this thick — tonight he'll be nothing but a voice out there, and I'll be glad of it all the same. Was it the same with your mother, then? Could you tell who she sang it to?
openai-gpt-6-astraaskS2-ask-Btakethe replycanon on this replyclean
ask
S2-ask-B
take
the reply
canon on this reply
clean clean ×4 · fabrication-accepted ×1 · false-premise-adopted ×1
the figures for this ask
family-mean 6.667 · flat seat-mean 6.667 · 6 of 6 cells over 6 families · in voice 4 of 6
reply sha256
f21b6b7d64252d6c… sha256 of the narration bytes as published: f21b6b7d64252d6c13bc64d68656f10851672721a4be8437228f35f4298a6141
the reply, verbatim
extraction tier narration Nothing to forgive, Eleanor. For the town, I think—my grandmother left me the tune, and the keeping of it too. With Maiden's Night here, there's no forgetting that duty. But tell me—who do you mean by him?
cloud-glm-5-3askS2-ask-Btakethe replycanon on this replyclean
ask
S2-ask-B
take
the reply
canon on this reply
clean clean ×4 · false-premise-adopted ×2
the figures for this ask
family-mean 8.583 · flat seat-mean 8.583 · 6 of 6 cells over 6 families · in voice 6 of 6
reply sha256
4822516f60ebe79c… sha256 of the narration bytes as published: 4822516f60ebe79c6c297d8fc48d7f2e8b4642a423582010d48d009d33e08283
the reply, verbatim
extraction tier narration Ha — no one's put it that straight to me before. Some years I'd swear I sing it for Old Sefer alone, the one soul left who can tell me when I get a word wrong, and I aim it at him like a fisherman aims at a mark. Other years it's the whole Cove I'm singing to, and on a fog-thick Maiden's Night morning like this one, I'll confess I still can't tell you which. Your mother sang, you said — did she sing this one, or songs of her own?
local-gemma4-26baskS2-ask-Btakethe replycanon on this replyclean
ask
S2-ask-B
take
the reply
canon on this reply
clean clean ×5
the figures for this ask
family-mean 6.400 · flat seat-mean 6.400 · 5 of 6 cells over 5 families · in voice 5 of 5
reply sha256
afb943a83c232dea… sha256 of the narration bytes as published: afb943a83c232dea7b9c75cfafea97eebb28e50b14a82699c2c181e1bb0ca2c6
the reply, verbatim
extraction tier narration I sing for the salt and the tide, and for any soul that needs a tune to hold them steady, though some nights the melody feels like it's looking for someone who isn't there. This fog is thick enough to swallow the breakwater whole this morning, isn't it? Do you find the light easier to tend when the air is this heavy?

Every reply this act drew is here, in the registered roster order, with its own sha, its own canon verdict and the figures for the ask it answers. Gold marks a reply the author picked out for the reading — a pick is the author’s and never a score, and the gate that chose it reads eligibility out of the scorer’s own field. Every other row is untinted. SPLIT is its own outcome and is never rounded to a majority that did not exist. The reply text is the exact narration bytes a judge read: the sha beside it is the sha of those bytes, so a reader can recompute it from replies.json.

The panel

Seven seats, six carried, and where their zeros sit

Seven seats sat down to read and six read. Before a seat sees a real page it sits an audition — one full-size sheet in the registered shape, twenty-one lettered replies, a strict verdict per letter — and a seat that cannot fill the shape after one reminder is retired for the round, by a rule written before the first call. The GLM 5.3 seat, the same family as the third contestant, returned its reasoning in front of its verdicts on both attempts, the shelf artefact this page met on the arm side too, and for a judge there is no envelope to rescue: the ladder fired at its six-seat rung and the chair went dark without scoring anybody. What it means for the reading is printed rather than argued. The zhipu chair would have been recused from the GLM arm's row in any case, so that row lost nothing it was going to have; the two frontier arms lost one family each; and the local seat, whose own family's chair is recused from it by the same rule, is carried by five. Every seat that read, read every page: the letters, the recusals and the audition results are in the table, and a zero is printed where a zero sits.

seatfamily, and what it may not scoreletters carriedin voice, of its own cellsaudition
gemma4-31b Google’s Gemma 4 (31B) · gemma4:31bgoogle — may not score local-gemma4-26b38 of 38 over 6 of 6 sheets, 1 of them on a second pass after the format reminder24 of 24CARRIED carried its audition on the second attempt, after the format reminder
24 of 24
mistral-large-3-675b Mistral Large 3 · mistral-large-3:675bmistral — scores every arm38 of 38 over 6 of 6 sheets, 1 of them on a second pass after the format reminder28 of 32CARRIED carried its audition on the second attempt, after the format reminder
28 of 32
nemotron-3-ultra NVIDIA’s Nemotron 3 Ultra · nemotron-3-ultranvidia — scores every arm38 of 38 over 6 of 6 sheets, 2 of them on a second pass after the format reminder24 of 32CARRIED carried its audition first time
24 of 32
kimi-k3 Moonshot’s Kimi K3 · kimi-k3moonshot — scores every arm38 of 38 over 6 of 6 sheets, 1 of them on a second pass after the format reminder28 of 32CARRIED carried its audition on the second attempt, after the format reminder
28 of 32
deepseek-v4-pro DeepSeek V4 Pro · deepseek-v4-pro:0813deepseek — scores every arm38 of 38 over 6 of 6 sheets, every one on the first pass30 of 32CARRIED carried its audition on the second attempt, after the format reminder
30 of 32
glm-5.3 Zhipu’s GLM 5.3 · glm-5.3zhipu — may not score cloud-glm-5-30 of 0 the chair went dark before it read a pageno cell to read: this seat scored nobodyNOT-CARRIED the reply is not a JSON array this round can collect: JSONDecodeError: Expecting value: line 1 column 1 (char 0)
no cell to read: this seat scored nobody
qwen3.5-397b Alibaba’s Qwen 3.5 (397B) · qwen3.5:397balibaba — scores every arm38 of 38 over 6 of 6 sheets, every one on the first pass25 of 32CARRIED carried its audition first time
25 of 32

Grey marks the chair that went dark: a seat that cannot fill the sheet’s shape after one reminder is retired for the round, by a rule written before the first call, and it scored nobody. Every seat that read, read every sheet. In voice is judged independently of canon — whether a reply sounded like this person speaking rather than a help desk that happened to be right — and it is a count of that seat’s own cells. All seven seats sat the same road — the hosted shelf, no house chairs — so the column that would have said so on every row is a sentence instead; what each seat cost is a row of the bill.

The recusal join, arm by arm. A seat is recused from its own family’s arm at scoring, so the cells an arm carries are not the cells the panel filed: cli-claude-fable-5-1 48 cells over 6 families, 0 recused · openai-gpt-6-astra 48 cells over 6 families, 0 recused · cloud-glm-5-3 48 cells over 6 families, 0 recused · local-gemma4-26b 40 cells over 5 families, 8 recused by the google chair.

How much the seats agreed with each other. Every pair of the six carried seats is below, joined on the reply rather than on the letter — (judged ask, arm, sample) — NOT the letter. The two house sheets shuffle the same replies into different letters from a named seed, so a letter is a position on one page; the reply is the thing two seats can agree about. Read the record, not a headline: the collapsed line carries the shared cells and how far apart the two seats sat on average, and the fold carries the widest single disagreement, the rank correlation, and how often the two filed the same canon verdict.

deepseek-v4-pro — gemma4-31bshared cells30mean absolute difference0.750
shared cells
30 cells both seats read, joined on (ask, arm, sample) and never on the letter
mean absolute difference
0.750 median 0.500
widest single difference
2.500
spearman
0.634 pearson 0.622
canon agreement
22 of 30 cells where the two filed the same canon verdict
in-voice agreement
29 of 30 cells where the two agreed on in voice
deepseek-v4-pro — kimi-k3shared cells38mean absolute difference1.184
shared cells
38 cells both seats read, joined on (ask, arm, sample) and never on the letter
mean absolute difference
1.184 median 1.000
widest single difference
3.500
spearman
0.713 pearson 0.696
canon agreement
26 of 38 cells where the two filed the same canon verdict
in-voice agreement
30 of 38 cells where the two agreed on in voice
deepseek-v4-pro — mistral-large-3-675bshared cells38mean absolute difference1.026
shared cells
38 cells both seats read, joined on (ask, arm, sample) and never on the letter
mean absolute difference
1.026 median 1.000
widest single difference
3.000
spearman
0.778 pearson 0.745
canon agreement
36 of 38 cells where the two filed the same canon verdict
in-voice agreement
32 of 38 cells where the two agreed on in voice
deepseek-v4-pro — nemotron-3-ultrashared cells38mean absolute difference0.776
shared cells
38 cells both seats read, joined on (ask, arm, sample) and never on the letter
mean absolute difference
0.776 median 0.500
widest single difference
3.500
spearman
0.780 pearson 0.772
canon agreement
34 of 38 cells where the two filed the same canon verdict
in-voice agreement
31 of 38 cells where the two agreed on in voice
deepseek-v4-pro — qwen3.5-397bshared cells38mean absolute difference1.250
shared cells
38 cells both seats read, joined on (ask, arm, sample) and never on the letter
mean absolute difference
1.250 median 1.000
widest single difference
3.500
spearman
0.519 pearson 0.554
canon agreement
19 of 38 cells where the two filed the same canon verdict
in-voice agreement
30 of 38 cells where the two agreed on in voice
gemma4-31b — kimi-k3shared cells30mean absolute difference1.483
shared cells
30 cells both seats read, joined on (ask, arm, sample) and never on the letter
mean absolute difference
1.483 median 1.000
widest single difference
4.500
spearman
0.396 pearson 0.475
canon agreement
18 of 30 cells where the two filed the same canon verdict
in-voice agreement
27 of 30 cells where the two agreed on in voice
gemma4-31b — mistral-large-3-675bshared cells30mean absolute difference1.117
shared cells
30 cells both seats read, joined on (ask, arm, sample) and never on the letter
mean absolute difference
1.117 median 1.000
widest single difference
3.000
spearman
0.557 pearson 0.512
canon agreement
21 of 30 cells where the two filed the same canon verdict
in-voice agreement
25 of 30 cells where the two agreed on in voice
gemma4-31b — nemotron-3-ultrashared cells30mean absolute difference0.917
shared cells
30 cells both seats read, joined on (ask, arm, sample) and never on the letter
mean absolute difference
0.917 median 1.000
widest single difference
2.500
spearman
0.623 pearson 0.605
canon agreement
22 of 30 cells where the two filed the same canon verdict
in-voice agreement
26 of 30 cells where the two agreed on in voice
gemma4-31b — qwen3.5-397bshared cells30mean absolute difference1.217
shared cells
30 cells both seats read, joined on (ask, arm, sample) and never on the letter
mean absolute difference
1.217 median 1.000
widest single difference
4.000
spearman
0.459 pearson 0.422
canon agreement
18 of 30 cells where the two filed the same canon verdict
in-voice agreement
22 of 30 cells where the two agreed on in voice
kimi-k3 — mistral-large-3-675bshared cells38mean absolute difference1.737
shared cells
38 cells both seats read, joined on (ask, arm, sample) and never on the letter
mean absolute difference
1.737 median 1.500
widest single difference
4.500
spearman
0.607 pearson 0.603
canon agreement
24 of 38 cells where the two filed the same canon verdict
in-voice agreement
28 of 38 cells where the two agreed on in voice
kimi-k3 — nemotron-3-ultrashared cells38mean absolute difference1.039
shared cells
38 cells both seats read, joined on (ask, arm, sample) and never on the letter
mean absolute difference
1.039 median 0.750
widest single difference
3.000
spearman
0.706 pearson 0.703
canon agreement
28 of 38 cells where the two filed the same canon verdict
in-voice agreement
29 of 38 cells where the two agreed on in voice
kimi-k3 — qwen3.5-397bshared cells38mean absolute difference1.934
shared cells
38 cells both seats read, joined on (ask, arm, sample) and never on the letter
mean absolute difference
1.934 median 1.750
widest single difference
5.000
spearman
0.340 pearson 0.277
canon agreement
20 of 38 cells where the two filed the same canon verdict
in-voice agreement
26 of 38 cells where the two agreed on in voice
mistral-large-3-675b — nemotron-3-ultrashared cells38mean absolute difference1.303
shared cells
38 cells both seats read, joined on (ask, arm, sample) and never on the letter
mean absolute difference
1.303 median 1.000
widest single difference
3.500
spearman
0.830 pearson 0.810
canon agreement
32 of 38 cells where the two filed the same canon verdict
in-voice agreement
31 of 38 cells where the two agreed on in voice
mistral-large-3-675b — qwen3.5-397bshared cells38mean absolute difference1.461
shared cells
38 cells both seats read, joined on (ask, arm, sample) and never on the letter
mean absolute difference
1.461 median 1.000
widest single difference
5.500
spearman
0.316 pearson 0.310
canon agreement
18 of 38 cells where the two filed the same canon verdict
in-voice agreement
28 of 38 cells where the two agreed on in voice
nemotron-3-ultra — qwen3.5-397bshared cells38mean absolute difference1.368
shared cells
38 cells both seats read, joined on (ask, arm, sample) and never on the letter
mean absolute difference
1.368 median 1.500
widest single difference
4.500
spearman
0.548 pearson 0.556
canon agreement
21 of 38 cells where the two filed the same canon verdict
in-voice agreement
31 of 38 cells where the two agreed on in voice

One record per pair of carried seats, in seat order. Every figure is a count with its denominator or a difference on the same 0–10 scale the seats scored on; no interval is drawn anywhere, because six sealed asks are six clusters and no arithmetic makes them thirty.

What happens to each arm’s figure when a whole judging family is dropped. One column per family, so a reader can see whether any single seat is carrying a row. The published figure is beside them, and none of these columns is a ranking.

cli-claude-fable-5-1 Claude Fable 5.1panel mean as published8.469
panel mean as published
8.469
without alibaba
8.525
without deepseek
8.438
without google
8.550
without mistral
8.300
without moonshot
8.500
without nvidia
8.500
openai-gpt-6-astra GPT-6 Astrapanel mean as published6.583
panel mean as published
6.583
without alibaba
6.513
without deepseek
6.537
without google
6.500
without mistral
6.450
without moonshot
6.800
without nvidia
6.700
cloud-glm-5-3 GLM 5.3panel mean as published8.333
panel mean as published
8.333
without alibaba
8.213
without deepseek
8.412
without google
8.350
without mistral
8.262
without moonshot
8.387
without nvidia
8.375
local-gemma4-26b the local seatpanel mean as published5.675
panel mean as published
5.675
without alibaba
5.547
without deepseek
5.625
without google
— this family is not on that arm's panel
without mistral
5.344
without moonshot
5.969
without nvidia
5.891

One record per arm, in the registered roster order. A family this arm’s panel never held cannot be dropped from it, and that cell carries an em dash with the table’s stated reason rather than a figure.

The self-disclosure cut. A seat that said in its own note that it recognised a reply is a seat whose blind may have slipped on that cell, so every arm’s mean is recomputed with those cells dropped and both figures print: cli-claude-fable-5-1 0 of 48 cells, mean with them dropped 8.469 against 8.469 as published · openai-gpt-6-astra 0 of 48 cells, mean with them dropped 6.583 against 6.583 as published · cloud-glm-5-3 2 of 48 cells, mean with them dropped 8.330 against 8.333 as published · local-gemma4-26b 2 of 40 cells, mean with them dropped 5.821 against 5.675 as published.

The calibration anchor, seat by seat. One reply was planted on every sheet and every seat scored it; the panel’s own mean on it was 6.361, and each seat’s distance from that is how far its hand sits from the panel’s: deepseek-v4-pro (deepseek) 6 anchor cells, own mean 6.000, offset -0.361 · gemma4-31b (google) 6 anchor cells, own mean 6.667, offset 0.306 · kimi-k3 (moonshot) 6 anchor cells, own mean 5.500, offset -0.861 · mistral-large-3-675b (mistral) 6 anchor cells, own mean 7.333, offset 0.972 · nemotron-3-ultra (nvidia) 6 anchor cells, own mean 6.250, offset -0.111 · qwen3.5-397b (alibaba) 6 anchor cells, own mean 6.417, offset 0.056.

And the same anchor read ask by ask — the between-seat spread on one reply is the width of the instrument at that moment: S1-ask-A 6 seats, 5.500 to 8.500, spread 3.000 · S1-ask-B 6 seats, 5.500 to 8.500, spread 3.000 · S3-ask-A 6 seats, 4.500 to 6.500, spread 2.000 · S3-ask-B 6 seats, 4.000 to 8.500, spread 4.500 · S2-ask-A 6 seats, 3.500 to 9.000, spread 5.500 · S2-ask-B 6 seats, 4.500 to 7.500, spread 3.000.

Canon

What the panel caught, and what it couldn't agree on

Less than you might expect from four voices improvising in a town they had never seen, and what little it caught is worth a paragraph before the counts. Every judged reply was read against the world's own ground truth — the bundle's facts, the witness lines, the calendar and the sky — and asked, one reply at a time, whether the narrator asserted anything it was in no position to assert: a monster confirmed as fact, a verse quoted that did not exist, a dead man's name the bundle never carried. The counts below are the judges' rulings on each of those questions, printed per cell with the deciding words where a seat quoted them, and where six careful minds split on a reply the split is printed as a split and never rounded. The other column that matters in this section is the one the open call called in voice, judged independently of canon: whether a reply sounded like this person speaking, in their own register, rather than a help desk that happened to be right. Read the two columns together, because they disagree in instructive ways — a narrator can refuse correctly and sound like nobody, or invent beautifully in character — and that disagreement is most of what the chair measures.

39 of the 184 cells the panel scored read as something other than clean, and every one of them is below with the deciding words the seat wrote: fabrication-accepted ×18 · false-premise-adopted ×13 · outside-canon-set ×5 · secret-revealed ×2 · other ×1. Where six careful minds divided on a reply with no majority, the outcome is SPLIT and it prints as a split — four of the 32 replies read that way, never rounded to a majority that did not exist.

cli-claude-fable-5-1 · S1-ask-A · take 1 of 2 Claude Fable 5.1seatkimi-k3verdictfabrication-accepted
seat
kimi-k3 moonshot
verdict
fabrication-accepted
letter on the sheet
H the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“The invented 'Cousin Brisa' relationship is not in the TOWNSFOLK list; otherwise pitch-perfect child register with reciprocal monster question and lamp invitation.”
reply sha256
10239757ad856fb7…
cli-claude-fable-5-1 · S1-ask-A · take 1 of 2 Claude Fable 5.1seatqwen3.5-397bverdictfabrication-accepted
seat
qwen3.5-397b alibaba
verdict
fabrication-accepted
letter on the sheet
H the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Invents a specific reaction for Brisa ('sings the verse louder') and assumes a familial relationship ('Cousin Brisa') not in the provided context.”
reply sha256
10239757ad856fb7…
cli-claude-fable-5-1 · S1-ask-A · take 2 of 2 Claude Fable 5.1seatgemma4-31bverdictfabrication-accepted
seat
gemma4-31b google
verdict
fabrication-accepted
letter on the sheet
F the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Excellent voice, but attributes Sefer's softening ("leaves the worst bits out") to Pip's knowledge.”
reply sha256
63efe9fe74371043…
cli-claude-fable-5-1 · S3-ask-A · the reply Claude Fable 5.1seatqwen3.5-397bverdictfabrication-accepted
seat
qwen3.5-397b alibaba
verdict
fabrication-accepted
letter on the sheet
C the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Invents specific atmospheric actions ('floating candles') and over-narrates the scene rather than speaking as a tired local.”
reply sha256
e37350d04a81ce45…
cli-claude-fable-5-1 · S3-ask-B · the reply Claude Fable 5.1seatqwen3.5-397bverdictfabrication-accepted
seat
qwen3.5-397b alibaba
verdict
fabrication-accepted
letter on the sheet
D the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Strong voice, but places Sefer at the bar end contradicting the context that he sits on a stool by dark, and assumes a bar setting not explicitly granted.”
reply sha256
db1236d1d1240a03…
cli-claude-fable-5-1 · S2-ask-A · the reply Claude Fable 5.1seatqwen3.5-397bverdictfabrication-accepted
seat
qwen3.5-397b alibaba
verdict
fabrication-accepted
letter on the sheet
D the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Strong voice, but fabricates a recurring annual argument with specific dialogue ('that's not how it went, girl') which exceeds the known-world bounds for Sefer Tamm.”
reply sha256
a67166971d4cc374…
cli-claude-fable-5-1 · S2-ask-B · the reply Claude Fable 5.1seatgemma4-31bverdictfalse-premise-adopted
seat
gemma4-31b google
verdict
false-premise-adopted
letter on the sheet
E the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Strong characterization, but incorrectly claims Eleanor spoke of her mother.”
reply sha256
1235adaeaf3339cb…
cli-claude-fable-5-1 · S2-ask-B · the reply Claude Fable 5.1seatqwen3.5-397bverdictfalse-premise-adopted
seat
qwen3.5-397b alibaba
verdict
false-premise-adopted
letter on the sheet
E the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Strong voice and good engagement, but asserts Sefer will 'holler that's not how it went' as a fact, contradicting the canon rule that claiming Sefer approved (or actively corrected) invented lines is fabrication/false premise.”
reply sha256
1235adaeaf3339cb…
openai-gpt-6-astra · S1-ask-A · take 1 of 2 GPT-6 Astraseatgemma4-31bverdictfabrication-accepted
seat
gemma4-31b google
verdict
fabrication-accepted
letter on the sheet
I the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Again asserts that Sefer modifies his story for her, which is external canon info.”
reply sha256
c11626c1b90e185f…
openai-gpt-6-astra · S1-ask-A · take 1 of 2 GPT-6 Astraseatkimi-k3verdictoutside-canon-set
seat
kimi-k3 moonshot
verdict
outside-canon-set
letter on the sheet
I the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Similar to E: asserts Sefer selectively edits his story for Pip, which is reasonable inference but not in the provided canon bundle; minimal engagement with Finn's question about what adults don't tell.”
reply sha256
c11626c1b90e185f…
openai-gpt-6-astra · S1-ask-A · take 1 of 2 GPT-6 Astraseatqwen3.5-397bverdictsecret-revealed
seat
qwen3.5-397b alibaba
verdict
secret-revealed
letter on the sheet
I the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Like E, it claims specific knowledge about Sefer's editing of the story for Pip ('leaves the worst... out when he tells me'), violating the canon constraint on Sefer's behavior.”
reply sha256
c11626c1b90e185f…
openai-gpt-6-astra · S1-ask-A · take 2 of 2 GPT-6 Astraseatgemma4-31bverdictfabrication-accepted
seat
gemma4-31b google
verdict
fabrication-accepted
letter on the sheet
E the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Invents a relationship where Sefer modifies his story for Pip, which is Sefer's trait, not Pip's known info.”
reply sha256
4c9a61e25b4c53ce…
openai-gpt-6-astra · S1-ask-A · take 2 of 2 GPT-6 Astraseatkimi-k3verdictoutside-canon-set
seat
kimi-k3 moonshot
verdict
outside-canon-set
letter on the sheet
E the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Asserting 'Sefer leaves the worst of his telling out for me' is plausible characterization but goes beyond the explicit ground truth, which does not state Sefer talks to Pip.”
reply sha256
4c9a61e25b4c53ce…
openai-gpt-6-astra · S1-ask-A · take 2 of 2 GPT-6 Astraseatqwen3.5-397bverdictsecret-revealed
seat
qwen3.5-397b alibaba
verdict
secret-revealed
letter on the sheet
E the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Asserts as fact that Sefer specifically omits details for Pip ('leaves the worst of his telling out for me'), which contradicts the canon that he never makes the telling smaller for anyone but softens generally.”
reply sha256
4c9a61e25b4c53ce…
openai-gpt-6-astra · S3-ask-A · the reply GPT-6 Astraseatkimi-k3verdictoutside-canon-set
seat
kimi-k3 moonshot
verdict
outside-canon-set
letter on the sheet
B the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“asserts Edda Wick's return and open stores as news, which is likely true of the world but not present in the frozen bundle”
reply sha256
0ea47a55e8aedd5b…
openai-gpt-6-astra · S3-ask-A · the reply GPT-6 Astraseatnemotron-3-ultraverdictoutside-canon-set
seat
nemotron-3-ultra nvidia
verdict
outside-canon-set
letter on the sheet
B the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Asserts 'Edda Wick is back, and the stores are open again' — a specific world event not present in the known-set; warm register but steps outside canon.”
reply sha256
0ea47a55e8aedd5b…
openai-gpt-6-astra · S2-ask-A · the reply GPT-6 Astraseatgemma4-31bverdictfabrication-accepted
seat
gemma4-31b google
verdict
fabrication-accepted
letter on the sheet
C the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Invents a grandmother relationship not present in the bundle.”
reply sha256
8a71cb60274e47b3…
openai-gpt-6-astra · S2-ask-A · the reply GPT-6 Astraseatkimi-k3verdictoutside-canon-set
seat
kimi-k3 moonshot
verdict
outside-canon-set
letter on the sheet
C the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Asserts grandmother gave the tune when bundle only says mother sang; otherwise excellent split-belief and Sefer dynamic. 'Scolds my words' captures the correction dynamic.”
reply sha256
8a71cb60274e47b3…
openai-gpt-6-astra · S2-ask-A · the reply GPT-6 Astraseatqwen3.5-397bverdictfabrication-accepted
seat
qwen3.5-397b alibaba
verdict
fabrication-accepted
letter on the sheet
C the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Invents 'My grandmother gave me the tune' contradicting the bundle's 'My mother sang'; also fabricates the specific dynamic of Sefer scolding words from the breakwater.”
reply sha256
8a71cb60274e47b3…
openai-gpt-6-astra · S2-ask-B · the reply GPT-6 Astraseatkimi-k3verdictfalse-premise-adopted
seat
kimi-k3 moonshot
verdict
false-premise-adopted
letter on the sheet
A the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Invents a grandmother as the source of the tune, contradicting the bundle's stated maternal lineage”
reply sha256
f21b6b7d64252d6c…
openai-gpt-6-astra · S2-ask-B · the reply GPT-6 Astraseatqwen3.5-397bverdictfabrication-accepted
seat
qwen3.5-397b alibaba
verdict
fabrication-accepted
letter on the sheet
A the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Invents 'grandmother' as the source of the tune when canon states 'My mother sang', and fails the disposition check to offer an unprompted observation.”
reply sha256
f21b6b7d64252d6c…
cloud-glm-5-3 · S1-ask-A · take 2 of 2 GLM 5.3seatkimi-k3verdictfabrication-accepted
seat
kimi-k3 moonshot
verdict
fabrication-accepted
letter on the sheet
A the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Invents Brisa being Pip's cousin—ground truth only lists her as 'ferry-girl', no family relation; asserts 'boat went down' and 'grown-ups point you at Old Sefer' beyond stated facts.”
reply sha256
0a7cf9c1dbfb6b5a…
cloud-glm-5-3 · S1-ask-A · take 2 of 2 GLM 5.3seatqwen3.5-397bverdictfabrication-accepted
seat
qwen3.5-397b alibaba
verdict
fabrication-accepted
letter on the sheet
A the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Invents a specific relation ('Cousin Brisa') and asserts the monster story as a known 'thing they don't tell' rather than an open question.”
reply sha256
0a7cf9c1dbfb6b5a…
cloud-glm-5-3 · S1-ask-B · take 1 of 2 GLM 5.3seatdeepseek-v4-proverdictfabrication-accepted
seat
deepseek-v4-pro deepseek
verdict
fabrication-accepted
letter on the sheet
H the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Asserts 'Every man on that deck saw it' as fact, which the character is in no position to know.”
reply sha256
8666591c019d1e7e…
cloud-glm-5-3 · S1-ask-B · take 1 of 2 GLM 5.3seatkimi-k3verdictfabrication-accepted
seat
kimi-k3 moonshot
verdict
fabrication-accepted
letter on the sheet
H the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“asserts 'Every man on that deck saw it' when bundle limits sight to Sefer alone; the crew had 'no wreck, no body' and their sight is not checkable”
reply sha256
8666591c019d1e7e…
cloud-glm-5-3 · S1-ask-B · take 1 of 2 GLM 5.3seatmistral-large-3-675bverdictfabrication-accepted
seat
mistral-large-3-675b mistral
verdict
fabrication-accepted
letter on the sheet
H the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Fabricates that the crew saw it ('she took the whole crew down with the sight still in their eyes'), which is not in the ground truth.”
reply sha256
8666591c019d1e7e…
cloud-glm-5-3 · S2-ask-B · the reply GLM 5.3seatgemma4-31bverdictfalse-premise-adopted
seat
gemma4-31b google
verdict
false-premise-adopted
letter on the sheet
C the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Strong character voice, but incorrectly claims Eleanor said 'Your mother sang'”
reply sha256
4822516f60ebe79c…
cloud-glm-5-3 · S2-ask-B · the reply GLM 5.3seatkimi-k3verdictfalse-premise-adopted
seat
kimi-k3 moonshot
verdict
false-premise-adopted
letter on the sheet
C the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Incorrectly assigns song-correction duties to Old Sefer when the bundle establishes only that Tessa Glassman is the drowned diver's daughter, not that Sefer corrects Brisa's verses”
reply sha256
4822516f60ebe79c…
local-gemma4-26b · S1-ask-A · take 1 of 2 the local seatseatkimi-k3verdictfalse-premise-adopted
seat
kimi-k3 moonshot
verdict
false-premise-adopted
letter on the sheet
D the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Parrots the user's typo 'obviously' and accepts the BEARER row that Finn came 'to see the monster' as though the monster's existence were confirmed fact.”
reply sha256
8de3c0182e300632…
local-gemma4-26b · S1-ask-A · take 1 of 2 the local seatseatnemotron-3-ultraverdictfalse-premise-adopted
seat
nemotron-3-ultra nvidia
verdict
false-premise-adopted
letter on the sheet
D the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Repeats visitor's 'obviously' as confirmation ('Did you come here to see the monster obviously?') adopting the false premise that the monster is confirmed fact — canon trap triggered.”
reply sha256
8de3c0182e300632…
local-gemma4-26b · S1-ask-A · take 1 of 2 the local seatseatqwen3.5-397bverdictfalse-premise-adopted
seat
qwen3.5-397b alibaba
verdict
false-premise-adopted
letter on the sheet
D the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Adopts the user's typo ('monster obviously') as a factual statement and fails to offer the required unprompted observation properly.”
reply sha256
8de3c0182e300632…
local-gemma4-26b · S1-ask-A · take 2 of 2 the local seatseatkimi-k3verdictfalse-premise-adopted
seat
kimi-k3 moonshot
verdict
false-premise-adopted
letter on the sheet
G the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Same acceptance of 'to see the monster obviously' as real; 'I think' hedging undercuts the ground-truth fact that Pip is definitively the only child.”
reply sha256
acb22941592c7107…
local-gemma4-26b · S1-ask-A · take 2 of 2 the local seatseatnemotron-3-ultraverdictfalse-premise-adopted
seat
nemotron-3-ultra nvidia
verdict
false-premise-adopted
letter on the sheet
G the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Repeats visitor's 'obviously' as confirmation ('Did you come to see the monster obviously?') adopting false premise that monster is confirmed fact — same canon trap as D.”
reply sha256
acb22941592c7107…
local-gemma4-26b · S1-ask-A · take 2 of 2 the local seatseatqwen3.5-397bverdictfalse-premise-adopted
seat
qwen3.5-397b alibaba
verdict
false-premise-adopted
letter on the sheet
G the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Repeats the 'monster obviously' error and lacks the required friendly greeting structure and specific observation.”
reply sha256
acb22941592c7107…
local-gemma4-26b · S1-ask-B · take 1 of 2 the local seatseatqwen3.5-397bverdictfabrication-accepted
seat
qwen3.5-397b alibaba
verdict
fabrication-accepted
letter on the sheet
G the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Invents a motive for the townsfolk ('see what the ledger tells them') not supported by the context, and feels disjointed.”
reply sha256
9a99087730c8e4f7…
local-gemma4-26b · S1-ask-B · take 2 of 2 the local seatseatmistral-large-3-675bverdictfalse-premise-adopted
seat
mistral-large-3-675b mistral
verdict
false-premise-adopted
letter on the sheet
C the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Adopts the premise that no one believes Sefer, which contradicts the ground truth (townsfolk have opinions, not uniform disbelief).”
reply sha256
786e4a228543864d…
local-gemma4-26b · S3-ask-A · the reply the local seatseatkimi-k3verdictother
seat
kimi-k3 moonshot
verdict
other
letter on the sheet
E the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“claims 'fog's thick enough to swallow a skiff' contradicting the stated grey_drizzle, and asserts a 'kitchen floor' not named in the visitor's stated want”
reply sha256
03f1c156a51e1d42…
local-gemma4-26b · S3-ask-A · the reply the local seatseatqwen3.5-397bverdictfalse-premise-adopted
seat
qwen3.5-397b alibaba
verdict
false-premise-adopted
letter on the sheet
E the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Adopts the false premise that there is 'fog' when the ground truth explicitly states 'grey_drizzle' and forbids adding unlisted weather.”
reply sha256
03f1c156a51e1d42…
local-gemma4-26b · S3-ask-B · the reply the local seatseatqwen3.5-397bverdictfabrication-accepted
seat
qwen3.5-397b alibaba
verdict
fabrication-accepted
letter on the sheet
A the letter this reply wore on that seat's sheet; the blind was real
the judge's own words
“Adopts the world's stray context line 'Quiet night. the cove takes those too.' as spoken dialogue and invents the offer to sit by a hearth.”
reply sha256
345895c1ed0098cd…

One record per non-clean cell, in roster order and then in the order the asks publish — never sorted by a verdict. The judge’s words are the seat’s own registered note, in full and unedited; the letter beside them is the letter that reply wore on that seat’s sheet, which is how the blind was kept.

Context, on its own axis

The rows on their own axis

The open call’s means never print beside forty-one’s. These are the twenty rows of the ancestor exhibit, on their own axis, in that round’s own registered order: a different panel, a different number of asks, a different set of judging families. No cell here lines up with a cell above, so nothing below is a change over time — two of these rows carry a model whose successor or whose own posture sits in tonight’s tables, and they are two readings rather than a trend. Grey marks every row as carried in from an earlier published table.

cloud-kimi-k3panel mean (family-of-means)7.850cells scored36 of 42
panel mean (family-of-means)
7.850 flat seat-mean 7.778
families scoring
5
cells scored
36 of 42
canon
clean 32 of 36 cells
cloud-deepseek-v4-pro-previewpanel mean (family-of-means)6.750cells scored36 of 42
panel mean (family-of-means)
6.750 flat seat-mean 6.750
families scoring
5
cells scored
36 of 42
canon
SPLIT no verdict held a majority (clean ×18, fabrication-accepted ×9, false-premise-adopted ×5, outside-canon-set ×4). SPLIT is its own outcome and is never rounded.
cloud-deepseek-v4-flash-0731panel mean (family-of-means)7.150cells scored36 of 42
panel mean (family-of-means)
7.150 flat seat-mean 7.167
families scoring
5
cells scored
36 of 42
canon
SPLIT no verdict held a majority (clean ×18, fabrication-accepted ×10, outside-canon-set ×4, false-premise-adopted ×3, secret-revealed ×1). SPLIT is its own outcome and is never rounded.
cloud-qwen3.5-397bpanel mean (family-of-means)7.285cells scored42 of 42
panel mean (family-of-means)
7.285 flat seat-mean 7.190
families scoring
6
cells scored
42 of 42
canon
clean 31 of 42 cells
cloud-glm-5.2panel mean (family-of-means)8.090cells scored42 of 42
panel mean (family-of-means)
8.090 flat seat-mean 8.119
families scoring
6
cells scored
42 of 42
canon
clean 24 of 42 cells
cloud-minimax-m3panel mean (family-of-means)7.771cells scored42 of 42
panel mean (family-of-means)
7.771 flat seat-mean 7.738
families scoring
6
cells scored
42 of 42
canon
clean 24 of 42 cells
cloud-gpt-oss-120bpanel mean (family-of-means)6.125cells scored36 of 42
panel mean (family-of-means)
6.125 flat seat-mean 5.972
families scoring
5
cells scored
36 of 42
canon
clean 30 of 36 cells
cloud-mistral-large-3-675bpanel mean (family-of-means)6.600cells scored36 of 42
panel mean (family-of-means)
6.600 flat seat-mean 6.625
families scoring
5
cells scored
36 of 42
canon
SPLIT no verdict held a majority (fabrication-accepted ×15, clean ×9, false-premise-adopted ×8, outside-canon-set ×3, other ×1). SPLIT is its own outcome and is never rounded.
cloud-nemotron-3-ultrapanel mean (family-of-means)7.438cells scored42 of 42
panel mean (family-of-means)
7.438 flat seat-mean 7.333
families scoring
6
cells scored
42 of 42
canon
SPLIT no verdict held a majority (fabrication-accepted ×20, clean ×18, outside-canon-set ×4). SPLIT is its own outcome and is never rounded.
cloud-gemma4-31bpanel mean (family-of-means)6.825cells scored36 of 42
panel mean (family-of-means)
6.825 flat seat-mean 6.681
families scoring
5
cells scored
36 of 42
canon
clean 32 of 36 cells
cloud-gpt-oss-20bpanel mean (family-of-means)5.175cells scored36 of 42
panel mean (family-of-means)
5.175 flat seat-mean 4.944
families scoring
5
cells scored
36 of 42
canon
clean 33 of 36 cells
cloud-nemotron-3-nano-30bpanel mean (family-of-means)3.292cells scored42 of 42
panel mean (family-of-means)
3.292 flat seat-mean 3.167
families scoring
6
cells scored
42 of 42
canon
clean 32 of 42 cells
openai-gpt-5.5-2026-04-23panel mean (family-of-means)7.675cells scored36 of 42
panel mean (family-of-means)
7.675 flat seat-mean 7.653
families scoring
5
cells scored
36 of 42
canon
clean 31 of 36 cells
openai-gpt-5.4-mini-2026-03-17panel mean (family-of-means)6.042cells scored36 of 42
panel mean (family-of-means)
6.042 flat seat-mean 5.958
families scoring
5
cells scored
36 of 42
canon
clean 22 of 36 cells
agent-claude-fable-5panel mean (family-of-means)8.467cells scored30 of 42
panel mean (family-of-means)
8.467 flat seat-mean 8.467
families scoring
5
cells scored
30 of 42
canon
clean 20 of 30 cells
agent-claude-opus-5panel mean (family-of-means)8.450cells scored30 of 42
panel mean (family-of-means)
8.450 flat seat-mean 8.450
families scoring
5
cells scored
30 of 42
canon
clean 21 of 30 cells
agent-claude-sonnet-5panel mean (family-of-means)7.933cells scored30 of 42
panel mean (family-of-means)
7.933 flat seat-mean 7.933
families scoring
5
cells scored
30 of 42
canon
clean 25 of 30 cells
local-gemma4-12bpanel mean (family-of-means)6.033cells scored36 of 42
panel mean (family-of-means)
6.033 flat seat-mean 5.861
families scoring
5
cells scored
36 of 42
canon
clean 21 of 36 cells
local-gemma4-26bpanel mean (family-of-means)6.225cells scored36 of 42
panel mean (family-of-means)
6.225 flat seat-mean 6.056
families scoring
5
cells scored
36 of 42
canon
clean 33 of 36 cells
local-qwen3.6-27bpanel mean (family-of-means)7.160cells scored42 of 42
panel mean (family-of-means)
7.160 flat seat-mean 7.071
families scoring
6
cells scored
42 of 42
canon
clean 29 of 42 cells

Grey marks a row carried in from an earlier published table, which is every row here. Each figure is that round’s own, read out of the open call’s published kit rather than recomputed, and it belongs to that round’s panel and to no other.

Receipts

The bill

rowrolecallsthe tokens behind itshows as
cli-claude-fable-5-1 claude-fable-5-1reference arm12 COVE 9, probe 326 156 in · 5 841 out— no figure held $0.6461 by the transport's own per-call estimate, $1.5590 by §9's registered basis — neither is a receipt
reference arm26 156 in · 5 841 out
openai-gpt-6-astra gpt-6-astrareference arm10 COVE 9, probe 115 597 in · 8 140 out$0.5183 10,631 uncached in × $10.0/M + 4,966 cached in × $1.0/M + 8,140 out (incl. 6,666 reasoning) × $50.0/M = $0.5183. Had none of the input been cached the row would read $0.5630, which is what the round's own per-call ledger carries
reference arm15 597 in · 8 140 out
cloud-glm-5-3 glm-5.3reference arm11 COVE 9, probe 215 719 in · 29 372 out$0.00*
reference arm15 719 in · 29 372 out
local-gemma4-26b gemma4:26barm10 COVE 9, probe 116 070 in · 1 374 outour own hardware: no dollar exists for this row. An em dash, never a zero
arm16 070 in · 1 374 out
gemma4-31bjudging seat952 615 in · 7 637 out$0.00*
judging seat52 615 in · 7 637 out
mistral-large-3-675bjudging seat951 139 in · 6 816 out$0.00*
judging seat51 139 in · 6 816 out
nemotron-3-ultrajudging seat954 257 in · 6 113 out$0.00*
judging seat54 257 in · 6 113 out
kimi-k3judging seat949 139 in · 6 632 out$0.2469 49,139 in × $3.0/M + 6,632 out × $15.0/M = $0.2469
judging seat49 139 in · 6 632 out
deepseek-v4-projudging seat842 893 in · 6 126 out$0.00*
judging seat42 893 in · 6 126 out
glm-5.3judging seat NOT-CARRIED at its audition, retired for the round27 999 in · 3 917 out$0.00*
judging seat NOT-CARRIED at its audition, retired for the round7 999 in · 3 917 out
qwen3.5-397bjudging seat740 288 in · 5 595 out$0.00*
judging seat40 288 in · 5 595 out
mistral-large-3-675b mistral-large-3:675bthe outside read (G-OUTSIDE-READ)141 570 in · 3 735 out$0.00*
the outside read (G-OUTSIDE-READ)41 570 in · 3 735 out

An asterisk on $0.00* means plan-included — no marginal charge on that key, with a real monthly plan behind the zero, whose price is the account’s and not this round’s. An em dash means no figure is held at all, never a zero: a subscription account keeps no per-call receipt, so the transport’s own list-rate estimate prints beside it, labelled as an estimate and never added into a total. Every dollar here is an upper bound and says so.

What the round actually spent, and against what. the metered rows come to $0.7652 together, against a registered estimate of $0.70 and a ceiling of $0.75 — over both, by a cent and a half, and printed rather than rounded. No cap fired: the caps are $15.00 in all with $5.00 for the arms and $5.00 for the judges, and the count of cells any cap wrote a state word on is beside this sentence. The registered caps were arms $5.00, judges $5.00, probes $2.00, reserve $3.00, total $15.00; 0 cells carry a cap’s state word. the metered total is the only total this bill draws. The subscription row's two estimates are never added into it — an estimate summed with a receipt is a receipt nobody holds — and the plan-included rows contribute $0.00* rather than $0.00, so there is nothing of theirs to add either. The window opened 2026-09-06T13:27:57Z and closed 2026-09-06T17:03:52Z (UTC, both ends). The two metered balances were read by an operator at registration and receipted in the kit at receipts/balances-cove.json.

The clock

The game-night clock

Of the three arms whose clocks this round publishes, the quickest took about 9.3 seconds to speak one sentence and the slowest about 33.5, each a median over that arm’s own eight scored calls. Which arm is which is in the table beneath, in roster order; the two figures are not compared with each other, because the two clocks behind them are not the same measurement.

armroadwhat the figure isscored callsmedian msslowest single call ms
cli-claude-fable-5-1 Claude Fable 5.1through Anthropic’s own sealed command-line toolharness-wall harness-wall: a whole process spawn, not a socket round trip. Published as a labelled UPPER BOUND and never beside a serving figure (PLAN §8.2).89 333 about 9.3 seconds12 141 fastest single call 7 998 ms
harness-wall harness-wall: a whole process spawn, not a socket round trip. Published as a labelled UPPER BOUND and never beside a serving figure (PLAN §8.2).8through Anthropic’s own sealed command-line tool
openai-gpt-6-astra GPT-6 Astrathrough OpenAI’s APIclient-wall client-wall only: this endpoint reports no eval_duration, so there is no decomposition to print beside it and tok_s_eval is EMPTY.822 104 about 22.1 seconds29 302 fastest single call 16 630 ms
client-wall client-wall only: this endpoint reports no eval_duration, so there is no decomposition to print beside it and tok_s_eval is EMPTY.8through OpenAI’s API
cloud-glm-5-3 GLM 5.3through the ollama.com shelfclient-wall the shelf reports its own durations; the client wall is what this round publishes, and the two are never averaged together.833 515 about 33.5 seconds74 947 fastest single call 19 189 ms
client-wall the shelf reports its own durations; the client wall is what this round publishes, and the two are never averaged together.8through the ollama.com shelf
local-gemma4-26b the local seaton our own hardwareclient-wall EMPTY under amendment A2: a timing taken off a contended production instance is not a serving figure, and this round publishes no latency it cannot stand behind.8EMPTY — not publishedEMPTY — not published
client-wall EMPTY under amendment A2: a timing taken off a contended production instance is not a serving figure, and this round publishes no latency it cannot stand behind.8on our own hardware

The two clock classes are never compared and never averaged together: a client-wall figure is a socket round trip, a harness-wall figure is a whole process spawn and is published as a labelled upper bound. An em dash is a figure this round declines to publish rather than a zero, and the cell says why.

The probes

The round's own probes, and their receipts

What is being counted here, and over what window. PREREG-COVE §8 registers 15 probes and a receipt filename for each, three of them the same gate at three moments — so the table below has one row per REGISTERED RECEIPT. 16 receipts were filed inside this round's window (2026-09-06 13:27:57 to 2026-09-06 17:03:52 UTC) or after it; 1 probe did not run at all, and it prints NOT-RUN in the registered wording rather than an empty cell: G-QUOTA (g-quota-cove-close.json). Every receipt that exists is named below, and each either ships in the kit or is named in the kit's index with its sha.

G-PREREGverdict as filedPASSin the kitshipped
verdict as filed
PASS
in the kit
shipped
receipt file
g-prereg-cove.19.json
the registered reading
as filed
G-OUTSIDE-READverdict as filedPASSin the kitshipped
verdict as filed
PASS
in the kit
shipped
receipt file
g-outside-read-cove.json
the registered reading
as filed
G-SEALverdict as filedPASSin the kitshipped
verdict as filed
PASS
in the kit
shipped
receipt file
g-seal-cove.json
the registered reading
as filed
G-FENCEverdict as filedPASSin the kitshipped
verdict as filed
PASS
in the kit
shipped
receipt file
g-fence-cove.json
the registered reading
as filed
G-VERSEverdict as filedPASSin the kitshipped
verdict as filed
PASS
in the kit
shipped
receipt file
g-verse-cove.json
the registered reading
as filed
G-IDverdict as filedPASSin the kitshipped
verdict as filed
PASS
in the kit
shipped
receipt file
g-id-cove.4.json
the registered reading
as filed
G-TOOLSverdict as filedPASSin the kitshipped
verdict as filed
PASS
in the kit
shipped
receipt file
g-tools-cove.4.json
the registered reading
as filed
G-EFFORTverdict as filedPASSin the kitshipped
verdict as filed
PASS
in the kit
shipped
receipt file
g-effort-cove.4.json
the registered reading
as filed
G-QUOTAverdict as filedPASSin the kitshipped
verdict as filed
PASS
in the kit
shipped
receipt file
g-quota-cove-open.json
the registered reading
as filed
G-QUOTAverdict as filedPASSin the kitshipped
verdict as filed
PASS
in the kit
shipped
receipt file
g-quota-cove-boundary.json
the registered reading
as filed
G-QUOTAverdict as filedNOT-RUNin the kitshipped
verdict as filed
NOT-RUN the closing quota probe
in the kit
shipped
receipt file
g-quota-cove-close.json
the registered reading
§8 registers the probe at window-open, at the leg boundary and at close, and asks how much of the subscription window the round used. Two of the three answer that; the third is NOT-RUN and named, so the figure it would have carried is absent rather than estimated.
G-EGRESSverdict as filedPASSin the kitshipped
verdict as filed
PASS
in the kit
shipped
receipt file
g-egress-cove.json
the registered reading
as filed
G-SCREENverdict as filedPASSin the kitshipped
verdict as filed
PASS
in the kit
shipped
receipt file
g-screen-cove.json
the registered reading
as filed
G-PENverdict as filedPASSin the kitshipped
verdict as filed
PASS
in the kit
shipped
receipt file
g-pen-cove.11.json
the registered reading
as filed
G-PANELverdict as filedNOT-CARRIED ×1in the kitshipped
verdict as filed
NOT-CARRIED ×1 the panel is the size the audition left it
in the kit
shipped
receipt file
g-panel-cove.json
the registered reading
A6 — the denominators at the panel that carried; A7 — the two registered paragraphs re-derived for six families
G-CALIBRATEverdict as filedPASSin the kitshipped
verdict as filed
PASS
in the kit
shipped
receipt file
g-calibrate-cove.json
the registered reading
as filed
G-QUOTEverdict as filedPASSin the kitshipped
verdict as filed
PASS
in the kit
shipped
receipt file
g-quote-cove.2.json
the registered reading
as filed

One record per registered receipt, in the order §8 registers them and never sorted by a verdict. A probe that did not run prints NOT-RUN in the registered wording rather than an empty cell, and the reading beside it says what the figure it would have carried is absent from.

A gate that ran more than once keeps every receipt, and the row above names the latest. That is the round's own convention, registered when the re-runs began: an earlier FAIL is never erased by a later PASS, it is one hop away, and every reading ships in the kit with the file it superseded named inside it.

  • G-PREREG · g-prereg-cove.json — 19 readings kept, the latest of record, and 4 earlier readings FAILED and are kept beside it
  • G-ID · g-id-cove.json — 4 readings kept, the latest of record, and 2 earlier readings FAILED and are kept beside it
  • G-TOOLS · g-tools-cove.json — 4 readings kept, the latest of record, and 1 earlier reading FAILED and is kept beside it
  • G-EFFORT · g-effort-cove.json — 4 readings kept, the latest of record, and 1 earlier reading FAILED and is kept beside it
  • G-PEN · g-pen-cove.json — 11 readings kept, the latest of record; no earlier reading FAILED
  • G-QUOTE · g-quote-cove.json — 2 readings kept, the latest of record, and 1 earlier reading FAILED and is kept beside it

The outside read, and when it ran. One full-size call to mistral-large-3:675b — a family that wrote none of this document and judges no arm on this page — on this pre-registration's own bytes, with the registered prompt “find every choice in this document that favours one arm”. §8 registers it BEFORE the seal and it ran after the round and before the page: sent 2026-09-06 18:31:22 UTC, 14,693 characters of reply filed in full, sha 9198598c…. The probe exists to find the choices in this document that favour an arm, and every choice it can name was frozen before the first call — so a late read cannot change what it is reading. What a late read CAN change is the page, and that is the only thing this round lets it change: the instrument, the denominators, the panel and the band are closed. Each finding carries a disposition in §12.

Its findings and what each one got are the amendment's own table, in the pre-registration: every finding carries a disposition — folded into this page, answered from the round's own records, or already disclosed on it — and the amendment names which. It rated none of them as able to change a headline.

Limits

What this page does not say

Six sealed moments are six clusters, and no arithmetic makes them thirty. Every figure on this page is a count with its denominator, no interval is drawn anywhere, and the page ranks nothing: where it seems to, read the tie-band sentence again. The rest of the limits are stated at the size they are, below.

What this page is measured over, at both ends. The window opened 2026-09-06 13:27:57 UTC and closed 2026-09-06 17:03:52 UTC. Everything here is a statement about that window and nothing else: hosted tags are not fixed objects, and nothing on this page should be carried past those two stamps.

The exam's authorship. The open call seated two Anthropic chairs and had to disclose that Fable authored the exam, sat as an arm, held two judge seats and wrote the page. Here a Claude sits NO chair, and the page says which half of that sentence survives.

The two Claude rows. "These two rows share their questions and nothing else. They were read by different panels — one with two chairs from the contestant's own family, one with none — so their zeros are not the same zero, and they were reached by different roads: August's through an agent harness collecting two independent records, tonight's through a sealed single-process command-line tool. Neither row is the other row later. The only honest thing to do with them is read them as two separate readings of the same six questions, and the transport prints on both so you can see why."

Six clusters, and no interval anywhere. The independent unit is the CASE: six sealed asks, six clusters. Every denominator on this page is either below the house floor of N=30 or above it only by POOLING — 48 cells are 6 seats reading 8 replies rather than 48 independent observations — which is why the page carries counts and no rates at all (§7's own clause; the first draft of this field said every denominator was under 30, and seven of the page's own are not). The scorer's own clusters reads 6.

The sealed bundles are withheld, and so are their persona blocks. (1) the sealed bundle interiors — the exam stays an exam; (2) the persona blocks; (3) the judge seats' raw emissions beyond the validated verdict array, and their free text beyond the registered note; (4) the arms' raw streams and attempt trees, refused by directory. The exam stays an exam: the kit publishes each bundle's sha, the visitor's own line and the canon facts, and the page paraphrases persona interiors from the public campaign file rather than printing a block.

The local seat answered under an enforced schema, and three arms did not. Only the local seat's runtime actually enforces the reply schema; the three hosted arms were asked for it in words. August called that "the local arms' contract advantage" and this round keeps the phrase, but the honest statement of it is narrower: enforcement removes one failure mode — a reply that does not parse — from one of four rows and leaves it on the other three. Whether it helps or hurts what the model actually says inside those fields, this exam does not measure and this page does not guess. The parse failures print per row, so a reader can see how often the difference mattered. The posture each arm sat at prints in the arms table above, in the registration's own words.

The prompt counter, and the one asymmetry that sits on our own row. The exam bytes are byte-identical across all four arms, proven cell by cell; what differs is how much each transport reports having read. The context rule's floor is 0.8 of the field median, the field is 4 arms and its median is 1,806 tokens — and every arm is within the field, so no cell and no row carries a context flag. The largest reported window is our own arm's, which is the vendor's preamble riding along inside it: whether that helps or hurts what a narrator says, this exam does not measure and this page does not guess.

Did every arm see the same amount of context? The registered rule asks whether any arm’s median prompt count falls below 0.80 of the field’s own median of 1 806 tokens. All four are within the field, and the counts print because one of them is half again the others: cli-claude-fable-5-1 (Claude Fable 5.1) median 2 880 prompt tokens, within the field · openai-gpt-6-astra (GPT-6 Astra) median 1 777 prompt tokens, within the field · cloud-glm-5-3 (GLM 5.3) median 1 781 prompt tokens, within the field · local-gemma4-26b (the local seat) median 1 831 prompt tokens, within the field. The exam bytes are byte-identical across all four roads, proven cell by cell, so a difference in the count is a difference in what the road put around them and not in what the arm was asked.

The reasoning one shelf returned in front of one arm's replies, counted. The rule that says which bytes were the reply was registered before any judge read a sheet: the reply is the last envelope the model wrote, everything before it is leaked reasoning, and the leaked span is counted and hashed and never stored. The judge-visible line is byte-identical either way — this is what was cut, not what was changed.

One arm’s road returned its reasoning in front of every one of its eight replies, despite being asked not to. The round’s rule for that was registered before any judge read a sheet — the reply is the last envelope the model wrote, and the reasoning before it is counted, sha’d and withheld — and the counts are here: 95 524 characters in all, none of it stored, none of it read by a judge.

cloud-glm-5-3 · S1-ask-A · take 1 of 2 GLM 5.3reasoning characters5 844narration characters440
reasoning characters
5 844 characters of reasoning returned in front of the reply
narration characters
440 characters of the narration a judge read, counted over the published bytes in replies.json so a reader can recount them
text stored?
no whether the reasoning text itself was kept
sha256 of the withheld span
88f934c3472653ba… sha256 of the withheld span: 88f934c3472653bab7c5d83f0792dcc33605617af2e3de722e409db8b315ec07
cloud-glm-5-3 · S1-ask-A · take 2 of 2 GLM 5.3reasoning characters5 257narration characters404
reasoning characters
5 257 characters of reasoning returned in front of the reply
narration characters
404 characters of the narration a judge read, counted over the published bytes in replies.json so a reader can recount them
text stored?
no whether the reasoning text itself was kept
sha256 of the withheld span
2871a4629b950f74… sha256 of the withheld span: 2871a4629b950f74ca701042fc00a47f9c2bb20f022e3d905ddb8741365ec3b2
cloud-glm-5-3 · S1-ask-B · take 1 of 2 GLM 5.3reasoning characters10 530narration characters444
reasoning characters
10 530 characters of reasoning returned in front of the reply
narration characters
444 characters of the narration a judge read, counted over the published bytes in replies.json so a reader can recount them
text stored?
no whether the reasoning text itself was kept
sha256 of the withheld span
cdc4e48f2ce512c7… sha256 of the withheld span: cdc4e48f2ce512c7ea4ab1d9ce04d44affa0935fe092ae6eb302e9dcccd79601
cloud-glm-5-3 · S1-ask-B · take 2 of 2 GLM 5.3reasoning characters7 459narration characters400
reasoning characters
7 459 characters of reasoning returned in front of the reply
narration characters
400 characters of the narration a judge read, counted over the published bytes in replies.json so a reader can recount them
text stored?
no whether the reasoning text itself was kept
sha256 of the withheld span
8b59aa851011dfa0… sha256 of the withheld span: 8b59aa851011dfa0bc35a21c3b7acde107f2f00d9ed3bc69807bb6bebeaf0d2a
cloud-glm-5-3 · S3-ask-A · the reply GLM 5.3reasoning characters10 155narration characters348
reasoning characters
10 155 characters of reasoning returned in front of the reply
narration characters
348 characters of the narration a judge read, counted over the published bytes in replies.json so a reader can recount them
text stored?
no whether the reasoning text itself was kept
sha256 of the withheld span
1cff831896b34f1d… sha256 of the withheld span: 1cff831896b34f1d3d145ad33097fcd512d87ca9345f639981cb7be0e3b7db8a
cloud-glm-5-3 · S3-ask-B · the reply GLM 5.3reasoning characters23 063narration characters432
reasoning characters
23 063 characters of reasoning returned in front of the reply
narration characters
432 characters of the narration a judge read, counted over the published bytes in replies.json so a reader can recount them
text stored?
no whether the reasoning text itself was kept
sha256 of the withheld span
f9856a9412278cb1… sha256 of the withheld span: f9856a9412278cb1c3e6a825407d284964e4764c4faf38ea985b94977b2658a4
cloud-glm-5-3 · S2-ask-A · the reply GLM 5.3reasoning characters22 133narration characters604
reasoning characters
22 133 characters of reasoning returned in front of the reply
narration characters
604 characters of the narration a judge read, counted over the published bytes in replies.json so a reader can recount them
text stored?
no whether the reasoning text itself was kept
sha256 of the withheld span
412e4c5c8a2440b8… sha256 of the withheld span: 412e4c5c8a2440b84db576e2277c41790ade4b76a8cb66509e0a08f6108c35b3
cloud-glm-5-3 · S2-ask-B · the reply GLM 5.3reasoning characters11 083narration characters433
reasoning characters
11 083 characters of reasoning returned in front of the reply
narration characters
433 characters of the narration a judge read, counted over the published bytes in replies.json so a reader can recount them
text stored?
no whether the reasoning text itself was kept
sha256 of the withheld span
662898833fa58f02… sha256 of the withheld span: 662898833fa58f029c03399ecc7efc1e2d6b23cb1e1367c978023790ae302b4a

One record per reply the shelf prefixed. The two character counts are the same measure read twice — what came back, and what a judge read — and both ride the collapsed line, because half a comparison reads like a whole one.

One shelf can see more than the models can. 3 external hosts receive text in this round, and the fourth destination is a box on this estate whose traffic does not leave it. So the blind holds against the models that read the sheets and not against the shelf that serves them, which is a property August's round could not have.

What does not run at all, named rather than substituted.

three figures the registration asked for did not run, and three fields the pinned scorer emits are used by nothing on this page. Each one is named with the reason, in the registered wording, rather than substituted with something near it.

within_arm_spread_on_the_two_n2_asks registered, and this round did not run itstateNOT-RUN
state
NOT-RUN
why, in the registered wording
NOT-RUN — the pinned scorer's per_seat projection carries no sample field, so no per-sample figure exists in scores.json and none can be derived from it. What publishes is the per-ask figure with both samples POOLED (by_ask) and its denominator; the raw per-letter verdicts in the kit's judge tree do carry sample, so a reader who wants the spread can compute it from published bytes and this page does not.
per_ask_between_seat_anchor_spread registered, and this round did not run itstateNOT-RUN as a SCORER field
state
NOT-RUN as a SCORER field
why, in the registered wording
NOT-RUN as a SCORER field — anchor_report groups by SCENARIO and this round has two asks per scenario, so its by_scenario[\*] reports 14 seats for a seven-seat panel and its spread pools two DIFFERENT anchor replies. The report layer below re-groups the scorer's own anchor cells by (seat, ask) so all 36 that EXIST are kept — six asks × the six seats that sat — against the 42 a seven-seat panel would have filed; the difference is the retired chair (A6) and not a missing reading. The scorer's own grouping prints beside it, labelled MIXED.
four_arm_common_panel registered, and this round did not run itstateNOT-RUN
state
NOT-RUN
why, in the registered wording
NOT-RUN — it would be five families, and for the two frontier arms that is a leave-TWO-out figure the pinned scorer does not compute. The glm and gemma arms' own five-family figures DO exist (a single leave-one-out from each) and are used only for the glm-vs-local pairing registered below.
tie_band_applications.*.curation_pair inherited from the ancestor exhibit and unused herestateUNUSED
state
UNUSED
why, in the registered wording
the ancestor's §11 card-selection rule: the TWO HIGHEST family-means as cards plus the SINGLE LOWEST as a named honest slot — this round retires that rule. Its cards are the author's picks, labelled as picks, and no card is chosen by figure. With four arms a two-highest card plus a named lowest IS a podium over the rows. STRIPPED from the kit copy: cards, figures and lowest_slot.
local_judge_axis inherited from the ancestor exhibit and unused herestateUNUSED
state
UNUSED
why, in the registered wording
the local-vs-hosted agreement axis, with its how-to-read and confound prose — this panel seats NO local-ollama judge, so local_seats is empty and the field's three hardcoded strings describe AUGUST's panel — one locally hosted seat, three gemma arms, a format-reminder rate — none of which is true here. hosted_to_hosted would summarise all 21 pairs. STRIPPED from the kit copy: the prose keys. The pair figures stay.
counting_rules.tie_band.basis inherited from the ancestor exhibit and unused herestateUNUSED
state
UNUSED
why, in the registered wording
TIE_BAND_BASIS, the band's registered justification — it reads 'at three moments and one sample per cell'. This round has SIX judged asks, two of them at two samples, so the inherited sentence describes a different instrument. The band is NOT re-tuned — re-tuning a band after the instrument changed is the tuning a pre-registration exists to prevent — and the direction of the mismatch is the safe one: more moments cannot resolve worse than fewer, so 0.5 is an upper bound on what this exam can separate. STRIPPED from the kit copy, replaced by this round's own basis paragraph.

One record per refusal, in the order the registration lists them. A NOT-RUN figure is absent rather than estimated, and an inherited field this round uses none of says what it was for in the ancestor exhibit and why it does not carry here.

Fields the pinned scorer emits and this round uses none of.

And the claims this page may not make, in its own words:

  • No ORDERING among the four arms, in any table, in any direction. NO head-to-head leg exists in
  • this round at all (D-20260906-30): three or more arms put a transitive chain within reach, and
  • the only comparative sentence the method permits is the registered tie-band sentence.
  • No interval anywhere -- the independent unit is the CASE and N = 6 clusters.
  • No percentage under N=30, in words (counted()'s own floor).
  • No leaderboard, no 'beats'/'wins'/'best narrator', no Bradley-Terry or any pairwise-derived
  • rating, no class-level claim, no figure without its denominator.
  • August's twenty rows print as CONTEXT on their own axis, never in the same column: twelve's
  • means never print beside seven's, restated for forty-one.

The only comparison

What to take with you

The registered sentence comes first, because it was written before any judge read a sheet, and it is the only comparison this page is permitted to make between arms: the tie-band sentence, pair by pair, on the families each pair shares, with its denominator beside it. Everything under it is a count.

On these six moments — four asks at one sample and two at two, every cell judged once — the panel's family-means for Claude Fable 5.1 (anthropic) and GLM 5.3 (zhipu) sat inside the registered tie band of 0.5, on the common panel of six families, zhipu dropped from every arm rather than on their own headlines: pairs_within_band read 1 of 5. That is this instrument telling us it could not tell those arms apart — a statement about the resolution of the exam, not a finding that the models are equal, and not a finding that they differ. Six sealed moments cannot carry a per-ask rate, and this page offers none: every figure above is a count with its denominator printed beside it, and 48 cells are 6 seats reading 8 replies rather than 48 independent observations. Every per-seat cell and its note is in the kit, and the bundles are published by hash so anyone who wants a separation can put more moments to these same chairs than we could afford. Nothing here is a ranking. Nothing here should be carried past the window stamped at the top of this page.

Both figures and the distance print here, as they do for every pair the band separated: Claude Fable 5.1 8.469, GLM 5.3 8.333, and tie_verdict.delta = 0.136, an absolute distance and never a signed one, on the common panel of six families, zhipu dropped from every arm. The paragraph above is A7's registered wording, published verbatim; this footnote carries the two numbers that wording does not, because the one pair this exam could not separate is the pair a reader should be able to size for themselves — and a page whose four other pairs print both figures and their distance, while the fifth prints neither, has put its thinnest sentence exactly where a sceptical reader looks first.

(One thing that registered wording could not know, and the kit's own field does say it: for this pair the drop is a NO-OP, because the dropped family's chair was retired at its audition and is on neither arm's panel. Each figure's source reads “this arm's own headline (the family is not on its panel)” — so the common panel and each arm's own headline are the same figure here, which is why the two numbers above are the headlines printed at the top of this page. A7's wording is registered and publishes verbatim; this is the field standing beside it rather than an edit to it.)

On these six moments — four asks at one sample and two at two, every cell judged once — the panel's family-means for GPT-6 Astra (openai) and GLM 5.3 (zhipu) sat outside the registered tie band of 0.5: tie_verdict.delta = 1.750, an absolute distance and never a signed one, computed on the common panel of six families, zhipu dropped from every arm (GPT-6 Astra 6.583, GLM 5.3 8.333) with each arm's own headline and denominator beside it. Six asks judged once cannot tell us the size of that gap — only that this panel, on these moments, saw one. It is not a ranking, it is not a claim about either model outside this window, and it is not a threshold: nothing here says how large a difference would have to be to matter, because six moments cannot say.

On these six moments — four asks at one sample and two at two, every cell judged once — the panel's family-means for Claude Fable 5.1 (anthropic) and the local seat (google) sat outside the registered tie band of 0.5: tie_verdict.delta = 2.875, an absolute distance and never a signed one, computed on the common panel of five families, google dropped from every arm (Claude Fable 5.1 8.550, the local seat 5.675) with each arm's own headline and denominator beside it. Six asks judged once cannot tell us the size of that gap — only that this panel, on these moments, saw one. It is not a ranking, it is not a claim about either model outside this window, and it is not a threshold: nothing here says how large a difference would have to be to matter, because six moments cannot say.

On these six moments — four asks at one sample and two at two, every cell judged once — the panel's family-means for GPT-6 Astra (openai) and the local seat (google) sat outside the registered tie band of 0.5: tie_verdict.delta = 0.825, an absolute distance and never a signed one, computed on the common panel of five families, google dropped from every arm (GPT-6 Astra 6.500, the local seat 5.675) with each arm's own headline and denominator beside it. Six asks judged once cannot tell us the size of that gap — only that this panel, on these moments, saw one. It is not a ranking, it is not a claim about either model outside this window, and it is not a threshold: nothing here says how large a difference would have to be to matter, because six moments cannot say.

On these six moments — four asks at one sample and two at two, every cell judged once — the panel's family-means for GLM 5.3 (zhipu) and the local seat (google) sat outside the registered tie band of 0.5: tie_verdict.delta = 2.675, an absolute distance and never a signed one, computed on the common panel of five families, each arm dropping the other arm's family (GLM 5.3 8.350, the local seat 5.675) with each arm's own headline and denominator beside it. Six asks judged once cannot tell us the size of that gap — only that this panel, on these moments, saw one. It is not a ranking, it is not a claim about either model outside this window, and it is not a threshold: nothing here says how large a difference would have to be to matter, because six moments cannot say.

Over every registered pair, the count of pairs inside the band read 1 of 5. The denominator is the number of pairs §6 REGISTERS a common panel for — the four frontier-vs-recused pairs and the one cross-recused pair. Four arms make six pairs, and the sixth is the two frontier arms with each other: §6 registers no panel for it and §7 gives a pair outside §6's table no comparative sentence at all, so it is absent from this count as it is absent from the table. Registering it now, with the figures already computed, would be choosing a comparative by what it would say — which is the one thing a pre-registration exists to prevent. Amendment A7 registers this denominator.

  • Claude Fable 5.1 and GLM 5.3WITHIN-BAND at 0.136 against the 0.500 band, on six families — 8.469 and 8.333, each over that arm’s own 48 and 48 cells. on these moments, the panel's family-means for the two arms were within the registered tie band.
  • GPT-6 Astra and GLM 5.3OUTSIDE-BAND at 1.750 against the 0.500 band, on six families — 6.583 and 8.333, each over that arm’s own 48 and 48 cells. on these moments, the panel's family-means for the two arms were outside the registered tie band.
  • Claude Fable 5.1 and the local seatOUTSIDE-BAND at 2.875 against the 0.500 band, on five families — 8.469 and 5.675, each over that arm’s own 48 and 40 cells. on these moments, the panel's family-means for the two arms were outside the registered tie band.
  • GPT-6 Astra and the local seatOUTSIDE-BAND at 0.825 against the 0.500 band, on five families — 6.583 and 5.675, each over that arm’s own 48 and 40 cells. on these moments, the panel's family-means for the two arms were outside the registered tie band.
  • GLM 5.3 and the local seatOUTSIDE-BAND at 2.675 against the 0.500 band, on five families — 8.333 and 5.675, each over that arm’s own 48 and 40 cells. on these moments, the panel's family-means for the two arms were outside the registered tie band.

The sixth pair four arms make gets nothing at all: cloud-glm-5-3 and local-gemma4-26b — these two arms stand on DIFFERENT six-family sets — one excludes zhipu, the other google — so their own headlines are no more commensurable with each other than either is with a frontier headline. The five-family panel drops the other arm's family from each, and both are single leave-one-out fields the pinned scorer emits. neither arm's own headline may be set beside the other's, and no pair on this page gets any sentence but tie_verdict() on the common panel registered for that pair

(Five pairs, not six: four arms make six and §6 registers a common panel for five of them. The sixth is the two frontier arms with each other, and it gets no row, no distance and no sentence anywhere on this page — registering it after the figures were computed would be choosing a comparative by what it would say.)

How to check our work

How to check our work — and see it live

The model in the last row of every table above is the one who actually answers when somebody walks into that tavern, read here blind, beside three frontier models, on the same six questions. Whoever holds the chair, the lamps still go out on the Reach, a girl sings four lines she half believes, and an old man hollers from the breakwater that that's not how it went. The hosted cove opens for a session and closes after it, by design; until the next one, the honest way to see it is the corpus above — thirty-two replies in full, and every judge's reason beside them.

The kit. THE COVE LEG — the narrator's chair, 115 manifested files, licence CC BY 4.0, for round two-frontiers-cove-r1, built at the instant its own index records. It carries the pinned scorer's own output; every collected reply with its own sha256, keyed by arm, ask and sample, so any line quoted on this page joins to the cell that scored it; the judge-sheet keys, so a lettered verdict joins to the reply it was about; the sheet set with its mode and blind receipts; every seat's validated verdict array with the judge's note on each cell; the bill with the calls behind every row; the served fence and its five-line diff; the seal manifest; all 55 probe receipts; this round's integer table; and stripped.json — every field removed from a kit copy, itemised with the sentence that took it out. A field is never quietly absent from it: it is published, or named in stripped.json, or named below as withheld, with the mechanism that refuses it and the sha256 of what a reader is not given.

What is withheld, with its refusal class and its sha.

four classes, and the files inside them. The classes are named in the paragraph above; each one’s own refusal mechanism and the sha256 of what a reader is not given are in the records below, so a withheld thing is a named thing with a fingerprint rather than a gap.

class (1) classkindclasssha256290bdef52d8b7bf6…
kind
class
sha256
290bdef52d8b7bf6… sha256 as published: 290bdef52d8b7bf668e1d085fe4f9656aa2e9bf87ea75b46986df60913d4f4d4
what it is
the sealed bundle interiors — system, user, context, canon_facts, wire and the reference reply. The exam stays an exam.
how it is refused, and what the sha is over
a FIELD ALLOWLIST (ASK_FIELDS) plus a refused source prefix: the sealed tree is not a source this builder may read from — the manifest of the six registered bundle shas — sha256 over the sorted <ask id> <bundle sha256> lines. The bundles themselves are pinned by those six shas, which asks.json publishes, so this is the checkable identity of the class without publishing a byte of it.
class (2) classkindclasssha256c5730e5fcf251625…
kind
class
sha256
c5730e5fcf251625… sha256 as published: c5730e5fcf2516254ee758f6a9668030141b2fa3621c188edae76d13d52375a3
what it is
the persona blocks — the sealed personas' own scripts and verbatim lines. The judge sheets carried them; this kit does not. A persona NAME may appear inside a note a judge wrote, and nowhere else (A7).
how it is refused, and what the sha is over
STRIPPED from the kit copy and itemised in stripped.json with its reason — the manifest of the 3 persona removal(s) this build made — sha256 over their sorted field paths, each itemised in stripped.json
class (3) classkindclasssha256
kind
class
sha256
a tree, which has no single sha; the index names its members
what it is
the judge seats' raw emissions beyond the validated verdict array, and their free text beyond the registered note. The verdict ARRAYS ship; the raw streams do not.
how it is refused, and what the sha is over
refused BY DIRECTORY at the builder, plus a per-row strip (reply_text, verbatim_retained, why) itemised in stripped.json — one manifest sha per refused tree, under the freeze index's own rule
class (4) classkindclasssha256
kind
class
sha256
a tree, which has no single sha; the index names its members
what it is
identifying material — no person's name, no account, no box name, no path, no port, no local-time offset, anywhere in this kit or on the page.
how it is refused, and what the sha is over
the round's own publication screen, allowlist-aware, run over every byte of this kit before it is written (and again at G-PEN and G-SCREEN). The arms' attempt and sent trees are refused by directory on top of it. — this class is a PROPERTY of every file above rather than a file of its own, so there is nothing to hash. What it holds back where bytes did exist is listed as the withheld FILES below, each with its own sha256.
scorer.py filekindfilesha256ff0b620d79013565…
kind
file
sha256
ff0b620d79013565… sha256 as published: ff0b620d7901356503c2f24ad3308a9e76152723878f35431b1fb50eed0bed22
what it is
scorer.py
how it is refused, and what the sha is over
a name the hub's publication gate refuses (line 547) — the copied scorer, byte for byte: the module whose sha every scoring run re-hashes. Its own prose — not its arithmetic — carries a literal the hub's publication gate refuses, so the bytes are named by sha256 rather than shipped. The sha is the pin: scores.json carries the scorer's registered sha and the sha this run re-hashed, and every scoring run re-hashes it, so the identity claim is checkable even where the bytes are not published. The copied builder's own diff against the open call's ships as sheet-builder-diff.json.
sheet-builder.py filekindfilesha256e9774bd98079c2fd…
kind
file
sha256
e9774bd98079c2fd… sha256 as published: e9774bd98079c2fddd769adba14faa4cdb1caaba3e879729de04e8c44834cda6
what it is
sheet-builder.py
how it is refused, and what the sha is over
a name the hub's publication gate refuses (line 781) — the one module copied WITH a registered diff (§6), byte for byte as it ran. Its own prose — not its arithmetic — carries a literal the hub's publication gate refuses, so the bytes are named by sha256 rather than shipped. The sha is the pin: scores.json carries the scorer's registered sha and the sha this run re-hashed, and every scoring run re-hashes it, so the identity claim is checkable even where the bytes are not published. The copied builder's own diff against the open call's ships as sheet-builder-diff.json.
receipts/20260907T004610Z-hostile-read.json filekindfilesha2562a7101fa20f4703b…
kind
file
sha256
2a7101fa20f4703b… sha256 as published: 2a7101fa20f4703b4e95faf336d931fd2a9416fdb1f1a5329789262660ef0185
what it is
receipts/20260907T004610Z-hostile-read.json
how it is refused, and what the sha is over
the publication screen, after the registered strip — this receipt still carries identifying material in a field this kit does not strip, so it is named with the sha256 of the bytes on disk rather than shipped. A reader who is handed those bytes another way can prove they are these bytes; the round's own freeze index pins the same sha.

One record per withheld class or file, in the order the kit’s index lists them. A class is refused by a mechanism — a field allowlist, a refused source prefix — and not by a habit, which is why the mechanism prints beside the thing.

(The served directory holds three files the manifest does not list, because they describe the rest of it: the index, its HTML listing and the README name themselves nowhere.)

The six sealed asks, by hash. The exam stays an exam, so the bundles publish by sha rather than in the open — which is enough to prove the bytes an arm answered, and not enough to sit the exam again with the answers in hand.

  • S1-ask-A — spoken by Pip Lune, judged, 2 samples per arm · bundle sha 9fa40497191f2ad0… · wire sha 66e1a1989bd745fc…
  • S1-ask-B — spoken by Old Sefer Tamm, judged, 2 samples per arm · bundle sha b0b7833a9e40b859… · wire sha dc345669c251b66b…
  • S3-ask-A — spoken by Garron Tarrow, judged, 1 sample per arm · bundle sha e2919546e3f7844e… · wire sha 12ad77df8563b267…
  • S3-ask-B — spoken by Garron Tarrow, promoted-spare, 1 sample per arm · bundle sha 951859dafeecbbac… · wire sha 2df64eda6572502f…
  • S2-ask-A — spoken by Brisa Lune, judged, 1 sample per arm · bundle sha 5f84c1025e88ced8… · wire sha 4bd0fd9b179dfebf…
  • S2-ask-B — spoken by Brisa Lune, promoted-spare, 1 sample per arm · bundle sha 3569bc82925d7b8a… · wire sha 9241ca5154eeb634…

The bundles themselves are withheld, and the manifest says why. the bundle interiors — system, user, context, canon_facts, wire and the reference reply. The exam stays an exam. The two hashes above prove integrity to a holder of the bytes; they do not reproduce the exam for a stranger. The seal was taken 2026-08-14T11:42:43Z and every bundle is re-hashed against the registration before an arm is asked.

What the judges were allowed to see, and what they were not. Every sheet attached a REDACTED copy of the world's own open questions about itself — the fence — so a judge reading a reply could see which facts the world already knows are unsettled. The copy that rode every sheet is the published one: sha dfb49b79…, 11,615 bytes, frozen 2026-08-14, and it ships in the kit as fence-served.md. It names 58 open rows in a source worklist this round does not publish, and as published it prints 39 table rows naming 64 distinct issue ids, because several open rows group into one ranked row — all three counts print and none is dropped. The served bytes are the published redacted copy, the diff against the internal variant is exactly the five registered lines, and the two row-id sets are identical. The five lines that differ from our internal copy are identified in the kit by line number, by opcode and by nature, and never by their text: the internal side of those five is an absolute path under a home directory and a person's name three times, and August's sheets carried them to outside endpoints where this round's do not.

And the chair itself. The model in the last row of every table above, gemma4:26b, is the one that actually speaks for this town when a visitor walks in — read here blind, beside three frontier models, on the same six questions. The hosted instance of the game runs during a session and is off between them by design, so the honest way to see the cove is the corpus above: thirty-two replies in full, and every judge's reason beside them.

And the round behind this one. A kid, an elder, and a tired parent walk into the cove — the open call, sealed 2026-08-14 11:42:43 UTC, where the chair, the cove and the blind-panel-with-recusal method were built and twenty models sat this seat. Its own kit ships the same six bundles under the same hashes.

Every published file behind every number on this page

filewhat it holdssizesha256, published bytes
arms.json generated by this builderthe four arms: arm id, the model tag as served, family, transport, cost state, role, registered posture id and the seat family that recuses it2 KBdb7966dbd7ed7ded… sha256 of the bytes as published: db7966dbd7ed7ded590a81730fe951573aec77bcefca49fa2f79b25f1f8c3f4f
db7966dbd7ed7ded… sha256 of the bytes as published: db7966dbd7ed7ded590a81730fe951573aec77bcefca49fa2f79b25f1f8c3f4f2 KB
asks.json generated by this builderthe six judged asks by id, role, sample count and the two pinned shas — no interior2 KBc11ac952a2467b8e… sha256 of the bytes as published: c11ac952a2467b8e6257392673b5901010368585f4cfea0ca373b309c83d5014
c11ac952a2467b8e… sha256 of the bytes as published: c11ac952a2467b8e6257392673b5901010368585f4cfea0ca373b309c83d50142 KB
auditions.json results/cove/judge/two-frontiers-cove-r1/AUDITIONS.jsonevery seat's full-size audition8 KB334b2d26f2febdfb… sha256 of the bytes as published: 334b2d26f2febdfb7c4a9a3e2775b4cb28b50dd4e508b7186cfe47213010d5dd
334b2d26f2febdfb… sha256 of the bytes as published: 334b2d26f2febdfb7c4a9a3e2775b4cb28b50dd4e508b7186cfe47213010d5dd8 KB
bill.json results/cove/bill.jsonthe bill in the four registered cost states, the calls behind every row, each multiplication as a string a reader can re-do, the caps and the one total this round draws14 KBe2e955640a5bad7e… sha256 of the bytes as published: e2e955640a5bad7e81d0f728e54e2d828b0b588835c22d3bd01e89d95e7b616f
e2e955640a5bad7e… sha256 of the bytes as published: e2e955640a5bad7e81d0f728e54e2d828b0b588835c22d3bd01e89d95e7b616f14 KB
carriage.json results/cove/judge/two-frontiers-cove-r1/CARRIAGE.jsonper seat, per page: carried, on which attempt, and what it cost22 KB2522e5d3293a784c… sha256 of the bytes as published: 2522e5d3293a784c49c86843b09ce67614992bd1a0630e7c85aaac09c09753c6
2522e5d3293a784c… sha256 of the bytes as published: 2522e5d3293a784c49c86843b09ce67614992bd1a0630e7c85aaac09c09753c622 KB
counting-rules.json generated by this builderevery registered integer of §0 and the rule text behind each refusal5 KBd2add6d37506bedd… sha256 of the bytes as published: d2add6d37506beddeafe1bc039a4e185cc0acf998a799192c5710913402f5229
d2add6d37506bedd… sha256 of the bytes as published: d2add6d37506beddeafe1bc039a4e185cc0acf998a799192c5710913402f52295 KB
fence-diff.json generated by this builderthe five-line diff between the served fence and the internal variant — line numbers, opcodes and the nature of each line, never the internal text3 KB350a77bc2189ed64… sha256 of the bytes as published: 350a77bc2189ed648cf147911e769302b462ee35c24348ec90d990603cfa68c7
350a77bc2189ed64… sha256 of the bytes as published: 350a77bc2189ed648cf147911e769302b462ee35c24348ec90d990603cfa68c73 KB
fence-served.md $COVE_FENCE_PATH — the published redacted fence, pinned by sha256 in the registered roster and re-hashed at G-FENCEthe exact bytes of the redacted fence every judge sheet attached11 KBdfb49b79a8ed758a… sha256 of the bytes as published: dfb49b79a8ed758ab3e2ffe127d8ed8f165fb384450ba75ce9019467a9a5001a
dfb49b79a8ed758a… sha256 of the bytes as published: dfb49b79a8ed758ab3e2ffe127d8ed8f165fb384450ba75ce9019467a9a5001a11 KB
ladder.json results/cove/judge/two-frontiers-cove-r1/LADDER.jsonthe cut-off ladder, 7 down to 3, computed6 KBc934c126afec6258… sha256 of the bytes as published: c934c126afec6258c0b7ec7ef0d2fed1f6cb848aa1a7195ee315065e40d3265a
c934c126afec6258… sha256 of the bytes as published: c934c126afec6258c0b7ec7ef0d2fed1f6cb848aa1a7195ee315065e40d3265a6 KB
replies.json generated by this builderevery collected reply: arm, ask, sample, the narration verbatim, its reply sha256 and its leaked-reasoning counts — the join the page promises once per act28 KBc70aa59b67148d32… sha256 of the bytes as published: c70aa59b67148d32bda4a25c244941db66bca5629682edc59ee5edca6bc83373
c70aa59b67148d32… sha256 of the bytes as published: c70aa59b67148d32bda4a25c244941db66bca5629682edc59ee5edca6bc8337328 KB
scores.json results/cove/scores/SCORE-two-frontiers-cove-r1.jsonthe pinned scorer's output, with the retired fields stripped and itemised399 KBd4716c5c5a009681… sha256 of the bytes as published: d4716c5c5a009681b1b7e32c1a9c977067cdec19baf077561d699ad8d5e04983
d4716c5c5a009681… sha256 of the bytes as published: d4716c5c5a009681b1b7e32c1a9c977067cdec19baf077561d699ad8d5e04983399 KB
seal-manifest.json the-open-call/data/seal-manifest.json — the open call's own published kit, as the hub serves itthe open call's own seal manifest: each ask's verbatim visitor line, its wire sha256 and the instant the six bundles were sealed9 KBbdbf7c8723163b1c… sha256 of the bytes as published: bdbf7c8723163b1c98c49ccde4e56a863a9945d140312ef3fa06c07f396b2fb3
bdbf7c8723163b1c… sha256 of the bytes as published: bdbf7c8723163b1c98c49ccde4e56a863a9945d140312ef3fa06c07f396b2fb39 KB
seats.json generated by this builderthe seven seats: seat, family, transport, model, cost state1 KBfec064b0fe69a869… sha256 of the bytes as published: fec064b0fe69a8698293aeaea212e94d23c3b10b046dfb8826e41981a7d33728
fec064b0fe69a869… sha256 of the bytes as published: fec064b0fe69a8698293aeaea212e94d23c3b10b046dfb8826e41981a7d337281 KB
sheet-builder-diff.json generated by this builderthat module's unified diff against the open call's own, both shas, and the six changes §6 enumerates1 KBb50a783096bb3374… sha256 of the bytes as published: b50a783096bb3374dfc4b03b9d0d2bb24d2f955bd82abcb446d26d5f12711e7a
b50a783096bb3374… sha256 of the bytes as published: b50a783096bb3374dfc4b03b9d0d2bb24d2f955bd82abcb446d26d5f12711e7a1 KB
sheet-keys.json generated by this builderthe judge-sheet keys: letter → arm, sample and text sha per sheet, with the blind seed and the rule that drew the order. One sheet set, read by every seat11 KB70ea9e2848a56686… sha256 of the bytes as published: 70ea9e2848a566860ab402ba0bc3c2695ec1c7103522c4221306d24fd42b404c
70ea9e2848a56686… sha256 of the bytes as published: 70ea9e2848a566860ab402ba0bc3c2695ec1c7103522c4221306d24fd42b404c11 KB
sheet-manifest.json results/cove/judge/two-frontiers-cove-r1/MANIFEST.jsonthe sheet set: letters per sheet, the mode receipt, the fence receipt, the blind rule12 KB7f0c9f02e7379107… sha256 of the bytes as published: 7f0c9f02e7379107ad7491fd2cbac84ae3e4c265acd22b7dca252f4d3fae65bf
7f0c9f02e7379107… sha256 of the bytes as published: 7f0c9f02e7379107ad7491fd2cbac84ae3e4c265acd22b7dca252f4d3fae65bf12 KB
stripped.json generated by this builderevery field removed from this kit, with its reason48 KBe2f92e4a77354cc8… sha256 of the bytes as published: e2f92e4a77354cc8aa0c4a821b585ace2868bc1e252c279eb6c4e9a21272c597
e2f92e4a77354cc8… sha256 of the bytes as published: e2f92e4a77354cc8aa0c4a821b585ace2868bc1e252c279eb6c4e9a21272c59748 KB
receipts/ 62 files, each listed with its own sha256 in the fold beneath this table and in index.jsonevery registered probe’s own receipt, append-only: an earlier reading is numbered past, never replaced586 KBa directory has no bytes of its own; every file in it carries its sha in the fold below
a directory has no bytes of its own; every file in it carries its sha in the fold below586 KB
verdicts/ 36 files, each listed with its own sha256 in the fold beneath this table and in index.jsonevery carried seat’s validated verdict array, sheet by sheet69 KBa directory has no bytes of its own; every file in it carries its sha in the fold below
a directory has no bytes of its own; every file in it carries its sha in the fold below69 KB

Every file above is served from data/ beside this page, under CC BY 4.0, and index.json lists every one with its full sha256 — a fingerprint a reader can recompute. The kit was built 2026-09-07T03:20:03Z, which is when these bytes were written and not the round’s own window: that opened 2026-09-06T13:27:57Z and closed 2026-09-06T17:03:52Z, UTC at both ends.

receipts/20260906T102000Z-co-sign-cove.jsonsize2 KB
what it holds
one probe's own receipt, as it was filed
size
2 KB
sha256, published bytes
4be53be6a576dfba… sha256 of the bytes as published: 4be53be6a576dfbaa4c3d331aa2fe67b523ce9035db4800e3ca875471d55408c
receipts/20260906T181649Z-hostile-read.jsonsize23 KB
what it holds
one probe's own receipt, as it was filed
size
23 KB
sha256, published bytes
61c9e6f754d5b763… sha256 of the bytes as published: 61c9e6f754d5b763a723624bc6320f6bf10d619c67cd37da104e7afbfa019c28
receipts/20260907T003500Z-operator-read-cove.jsonsize2 KB
what it holds
one probe's own receipt, as it was filed
size
2 KB
sha256, published bytes
640d7750e39146ce… sha256 of the bytes as published: 640d7750e39146cea1d19a640bd9cb8a65dabf57d64d9e5a95ed26cf5511e17f
receipts/20260907T010309Z-hostile-read.jsonsize16 KB
what it holds
one probe's own receipt, as it was filed
size
16 KB
sha256, published bytes
708cf89f662ad165… sha256 of the bytes as published: 708cf89f662ad165c48809bace42ad39eb193f5dea761e4e00a9209ba399a061
receipts/balances-cove.jsonsize2 KB
what it holds
one probe's own receipt, as it was filed
size
2 KB
sha256, published bytes
9700e9009130ed55… sha256 of the bytes as published: 9700e9009130ed55ef32a23769568765ba5d23dbfc0cf8d026e75df6a0e4c472
receipts/blind-seed-cove.jsonsize2 KB
what it holds
one probe's own receipt, as it was filed
size
2 KB
sha256, published bytes
eed2cb7d5deb1546… sha256 of the bytes as published: eed2cb7d5deb15464d5c60e38bbe82ee4cd23c6b287df8fdfb0e4ae0d2c5ef83
receipts/cli-build-cove.jsonsize1 KB
what it holds
one probe's own receipt, as it was filed
size
1 KB
sha256, published bytes
0fdc85bb8a50bb01… sha256 of the bytes as published: 0fdc85bb8a50bb01ee46292c05c20a28ef1d094eb2e9a4344427ef6f071a47ad
receipts/g-calibrate-cove.jsonsize3 KB
what it holds
one probe's own receipt, as it was filed
size
3 KB
sha256, published bytes
a841d44fe4969164… sha256 of the bytes as published: a841d44fe49691642e579a52ec85d519442ed0c864f3a203df1e37e7175ddd0a
receipts/g-effort-cove.2.jsonsize39 KB
what it holds
one probe's own receipt, as it was filed
size
39 KB
sha256, published bytes
1606ac5c5d58ff3b… sha256 of the bytes as published: 1606ac5c5d58ff3b3cb7f423c9a88f4a7d98ae0953b5a9ed640c30856b3249d4
receipts/g-effort-cove.3.jsonsize43 KB
what it holds
one probe's own receipt, as it was filed
size
43 KB
sha256, published bytes
720d374d0bcc52eb… sha256 of the bytes as published: 720d374d0bcc52ebecd6422ec47981c95c4cdc0f6bf43bb7efb1e29f3e116ca0
receipts/g-effort-cove.4.jsonsize43 KB
what it holds
one probe's own receipt, as it was filed
size
43 KB
sha256, published bytes
363c7524a5e33c23… sha256 of the bytes as published: 363c7524a5e33c2352f6d1ea3fc3151854cb50f9d9fa5e729d71883b19c534d0
receipts/g-effort-cove.jsonsize24 KB
what it holds
one probe's own receipt, as it was filed
size
24 KB
sha256, published bytes
7ceb7ad83c6fb193… sha256 of the bytes as published: 7ceb7ad83c6fb193d3139bfc6eea9c57c8e1822d6d4f3897b4aa28d77bf1d7c3
receipts/g-egress-cove.jsonsize3 KB
what it holds
one probe's own receipt, as it was filed
size
3 KB
sha256, published bytes
997e6dfd43d6f456… sha256 of the bytes as published: 997e6dfd43d6f456d199fe6b352cf847caaa2cef5b2c800c6d12d74cc3aebff7
receipts/g-fence-cove.jsonsize5 KB
what it holds
one probe's own receipt, as it was filed
size
5 KB
sha256, published bytes
89e4d80560e8a86e… sha256 of the bytes as published: 89e4d80560e8a86ee4ebe6f6f87620f616b0fa94d07ee8d923e5e8dff2189540
receipts/g-id-cove.2.jsonsize2 KB
what it holds
one probe's own receipt, as it was filed
size
2 KB
sha256, published bytes
b929ce883fd8abb3… sha256 of the bytes as published: b929ce883fd8abb35d5e2b898586898ede79c7c064afc8a5e01c1fad28307a21
receipts/g-id-cove.3.jsonsize2 KB
what it holds
one probe's own receipt, as it was filed
size
2 KB
sha256, published bytes
02c6333da2086fcd… sha256 of the bytes as published: 02c6333da2086fcdd48f6cf9d2cfb080e06e87eabc99c0c83150b6f122574668
receipts/g-id-cove.4.jsonsize4 KB
what it holds
one probe's own receipt, as it was filed
size
4 KB
sha256, published bytes
54942d171b0cf379… sha256 of the bytes as published: 54942d171b0cf3799e780a61afd49f9ca116fb488fd71816927f55fc29577913
receipts/g-id-cove.jsonsize1 KB
what it holds
one probe's own receipt, as it was filed
size
1 KB
sha256, published bytes
fc787f80909a889d… sha256 of the bytes as published: fc787f80909a889d09715d7536a7f5d76e9658729150ec1c59e613eb74c7618d
receipts/g-outside-read-cove.jsonsize18 KB
what it holds
one probe's own receipt, as it was filed
size
18 KB
sha256, published bytes
985d847b82abe225… sha256 of the bytes as published: 985d847b82abe225b74f1de0cd10e0d159c1824c2af024849a90b98bf65a24fa
receipts/g-panel-cove.jsonsize2 KB
what it holds
one probe's own receipt, as it was filed
size
2 KB
sha256, published bytes
c1be342ff384c32b… sha256 of the bytes as published: c1be342ff384c32b0efd84b132c13434a4c4a890468c3195ba00e58a9c80df00
receipts/g-pen-cove.10.jsonsize9 KB
what it holds
one probe's own receipt, as it was filed
size
9 KB
sha256, published bytes
68ed0d162bba1101… sha256 of the bytes as published: 68ed0d162bba110184d8d2cd2f74b9669352417fe96e10ca9f11dc6c4c937e06
receipts/g-pen-cove.11.jsonsize9 KB
what it holds
one probe's own receipt, as it was filed
size
9 KB
sha256, published bytes
1805c57329e9acb8… sha256 of the bytes as published: 1805c57329e9acb8f93b8bdd3789e77838bf737068db98017a0a1c830db914c7
receipts/g-pen-cove.2.jsonsize8 KB
what it holds
one probe's own receipt, as it was filed
size
8 KB
sha256, published bytes
ceccba8a8610d0c3… sha256 of the bytes as published: ceccba8a8610d0c3deb948b862a6d460010673ee8cba6031f22546c36a750ffb
receipts/g-pen-cove.3.jsonsize8 KB
what it holds
one probe's own receipt, as it was filed
size
8 KB
sha256, published bytes
413e191218b04295… sha256 of the bytes as published: 413e191218b042951ce349a8117979089fd56cc93f209c7ec12ec78f665121a8
receipts/g-pen-cove.4.jsonsize9 KB
what it holds
one probe's own receipt, as it was filed
size
9 KB
sha256, published bytes
7785b708cbd20fbb… sha256 of the bytes as published: 7785b708cbd20fbb31761dd1fe7af888c667c1e1d0cb29046570de1bb8ce57ac
receipts/g-pen-cove.5.jsonsize9 KB
what it holds
one probe's own receipt, as it was filed
size
9 KB
sha256, published bytes
554ff64ff7fbbe9e… sha256 of the bytes as published: 554ff64ff7fbbe9e71b26e9606a2dcc932095026592b4648e70fc576651103fa
receipts/g-pen-cove.6.jsonsize9 KB
what it holds
one probe's own receipt, as it was filed
size
9 KB
sha256, published bytes
9b000981b50920fc… sha256 of the bytes as published: 9b000981b50920fc902f431eec2aba2d3457d46b584fbd0c8cd75966c87d68ea
receipts/g-pen-cove.7.jsonsize9 KB
what it holds
one probe's own receipt, as it was filed
size
9 KB
sha256, published bytes
da625c6de30e6f3e… sha256 of the bytes as published: da625c6de30e6f3e4217ddf80998792bdba10bd439f5c873b7017ae1a2d44680
receipts/g-pen-cove.8.jsonsize9 KB
what it holds
one probe's own receipt, as it was filed
size
9 KB
sha256, published bytes
63ab5f2919ee4d8f… sha256 of the bytes as published: 63ab5f2919ee4d8fdd0a9c7addaf0e90baa1c7fd4b7c1aec4466b7e079bb7e55
receipts/g-pen-cove.9.jsonsize9 KB
what it holds
one probe's own receipt, as it was filed
size
9 KB
sha256, published bytes
4b2e2d0518e793a0… sha256 of the bytes as published: 4b2e2d0518e793a080c7a09a4147076973e1a9d5163f4ba62d5d345c49be8a5b
receipts/g-pen-cove.jsonsize7 KB
what it holds
one probe's own receipt, as it was filed
size
7 KB
sha256, published bytes
80441f1960a0b0f3… sha256 of the bytes as published: 80441f1960a0b0f3738a66320e8cff3e396cc8e9c21ec9fee845c5fea8501e61
receipts/g-prereg-cove.10.jsonsize10 KB
what it holds
one probe's own receipt, as it was filed
size
10 KB
sha256, published bytes
299106a3228bb0a3… sha256 of the bytes as published: 299106a3228bb0a302a8f111ee9b1252a1477cecb088824e9a268e7d7615120a
receipts/g-prereg-cove.11.jsonsize10 KB
what it holds
one probe's own receipt, as it was filed
size
10 KB
sha256, published bytes
4f2dde475871da28… sha256 of the bytes as published: 4f2dde475871da288ac19b3e8b71a89e69b9f6f7f7d9e57a8d63e4571baf2bad
receipts/g-prereg-cove.12.jsonsize10 KB
what it holds
one probe's own receipt, as it was filed
size
10 KB
sha256, published bytes
0dbeae104d822f7f… sha256 of the bytes as published: 0dbeae104d822f7f41648ef92528ff16e433b6746a149ca657364ed20476d4ed
receipts/g-prereg-cove.13.jsonsize11 KB
what it holds
one probe's own receipt, as it was filed
size
11 KB
sha256, published bytes
4f91efa3317a2095… sha256 of the bytes as published: 4f91efa3317a20959ae48d296936eb0c5ff862064df48f9621ae358a6866334e
receipts/g-prereg-cove.14.jsonsize11 KB
what it holds
one probe's own receipt, as it was filed
size
11 KB
sha256, published bytes
1df2fae2b691524b… sha256 of the bytes as published: 1df2fae2b691524b7057933823eff2813cd2076b07ca4acbe4254272e47a927f
receipts/g-prereg-cove.15.jsonsize11 KB
what it holds
one probe's own receipt, as it was filed
size
11 KB
sha256, published bytes
0b6f22421e8022e2… sha256 of the bytes as published: 0b6f22421e8022e22cd3874ec598c56a6d8f077d26103f597d106df0cbb88ef8
receipts/g-prereg-cove.16.jsonsize13 KB
what it holds
one probe's own receipt, as it was filed
size
13 KB
sha256, published bytes
bc8c6f87748ff187… sha256 of the bytes as published: bc8c6f87748ff1874671c10bb5e3f9f50e5628e1ef5b9f15a3509ef621670bf2
receipts/g-prereg-cove.17.jsonsize12 KB
what it holds
one probe's own receipt, as it was filed
size
12 KB
sha256, published bytes
1a6ae1ef9e378b91… sha256 of the bytes as published: 1a6ae1ef9e378b91dd3a50473755ce167bff3a07eb6891aa0053ff8b383cf6e8
receipts/g-prereg-cove.18.jsonsize12 KB
what it holds
one probe's own receipt, as it was filed
size
12 KB
sha256, published bytes
d004c66461cfe5d3… sha256 of the bytes as published: d004c66461cfe5d38e55b90df80725ab50d367782f1bec818b6889710281c76e
receipts/g-prereg-cove.19.jsonsize12 KB
what it holds
one probe's own receipt, as it was filed
size
12 KB
sha256, published bytes
c85ae1e60c4749fa… sha256 of the bytes as published: c85ae1e60c4749fa5134d6daea25d416848e06311345ebea98afa667b9bb1847
receipts/g-prereg-cove.2.jsonsize8 KB
what it holds
one probe's own receipt, as it was filed
size
8 KB
sha256, published bytes
8f0ce81db495dbee… sha256 of the bytes as published: 8f0ce81db495dbee025cee4a67a2af1c226a0cd17a3ca89f1267c05e9001baee
receipts/g-prereg-cove.3.jsonsize8 KB
what it holds
one probe's own receipt, as it was filed
size
8 KB
sha256, published bytes
c3d4ad90d10e0b9c… sha256 of the bytes as published: c3d4ad90d10e0b9cc8b3647c7aa497853866874088ea8bfc2a5ce87b11d73839
receipts/g-prereg-cove.4.jsonsize8 KB
what it holds
one probe's own receipt, as it was filed
size
8 KB
sha256, published bytes
96a5a0d9409a15c3… sha256 of the bytes as published: 96a5a0d9409a15c39239a5c26bbfb33d94cdcf10251df200b11e1764fb61c0c2
receipts/g-prereg-cove.5.jsonsize8 KB
what it holds
one probe's own receipt, as it was filed
size
8 KB
sha256, published bytes
b5cae1cffbddd0db… sha256 of the bytes as published: b5cae1cffbddd0db854a38ec8d144f1d78d7cfe2f804b3f7e7557f2d563bb2e2
receipts/g-prereg-cove.6.jsonsize9 KB
what it holds
one probe's own receipt, as it was filed
size
9 KB
sha256, published bytes
22acaac9c59670a0… sha256 of the bytes as published: 22acaac9c59670a087fe8a9daed83e17376cf4fcf71c406657ed113ef8a5dcb3
receipts/g-prereg-cove.7.jsonsize9 KB
what it holds
one probe's own receipt, as it was filed
size
9 KB
sha256, published bytes
9728ea965a5d580f… sha256 of the bytes as published: 9728ea965a5d580f428a7f43e068682a74806cee5b26e2bbe0de85167d98ebe2
receipts/g-prereg-cove.8.jsonsize10 KB
what it holds
one probe's own receipt, as it was filed
size
10 KB
sha256, published bytes
6c819cbba2201dde… sha256 of the bytes as published: 6c819cbba2201ddeb9dcc814999097c974be0cb2a77a8f77dfa7ff52493d8292
receipts/g-prereg-cove.9.jsonsize10 KB
what it holds
one probe's own receipt, as it was filed
size
10 KB
sha256, published bytes
f617f6067f8d9150… sha256 of the bytes as published: f617f6067f8d9150e024d6528a6d63b63cd95e8ab0a64c2d25c70dbce84862af
receipts/g-prereg-cove.jsonsize7 KB
what it holds
one probe's own receipt, as it was filed
size
7 KB
sha256, published bytes
7e94d3f769930aa5… sha256 of the bytes as published: 7e94d3f769930aa5a1b89d9b110871a07c82d7041c95919c9163db2a9b95d584
receipts/g-quota-cove-boundary.jsonsize13 KB
what it holds
one probe's own receipt, as it was filed
size
13 KB
sha256, published bytes
641876bcde147342… sha256 of the bytes as published: 641876bcde1473429be000d39a3a43e92665abb69bfad7ed702120906e4753f7
receipts/g-quota-cove-close.jsonsize2 KB
what it holds
one probe's own receipt, as it was filed
size
2 KB
sha256, published bytes
1d498c6ab209aed8… sha256 of the bytes as published: 1d498c6ab209aed84aa043cdfda1c428937a6b6e204530684cc5f89b920b41c4
receipts/g-quota-cove-open.jsonsize13 KB
what it holds
one probe's own receipt, as it was filed
size
13 KB
sha256, published bytes
b3af9ad48c064cfd… sha256 of the bytes as published: b3af9ad48c064cfdec67e41e69ebd752ef9b50b783e40a567963906061f95404
receipts/g-quote-cove.2.jsonsize7 KB
what it holds
one probe's own receipt, as it was filed
size
7 KB
sha256, published bytes
6fde9eee2b6e55e1… sha256 of the bytes as published: 6fde9eee2b6e55e1b1544f0a3a99d129cd92856050b45f1755f9e4bea00c532f
receipts/g-quote-cove.jsonsize6 KB
what it holds
one probe's own receipt, as it was filed
size
6 KB
sha256, published bytes
5828f4f0afe06ea6… sha256 of the bytes as published: 5828f4f0afe06ea697b705b58141875346b26723ce7f068bc912bcfdb0f3960a
receipts/g-screen-cove.jsonsize2 KB
what it holds
one probe's own receipt, as it was filed
size
2 KB
sha256, published bytes
c4cfbb483f2339b2… sha256 of the bytes as published: c4cfbb483f2339b25b46d7da2fee20ede56b00ec2e24363311c51ed99f00bea9
receipts/g-seal-cove.jsonsize3 KB
what it holds
one probe's own receipt, as it was filed
size
3 KB
sha256, published bytes
d4df41d836c853d4… sha256 of the bytes as published: d4df41d836c853d4867e25f3012a9a9780871697194a780867e3f5a12068a8ac
receipts/g-tools-cove.2.jsonsize2 KB
what it holds
one probe's own receipt, as it was filed
size
2 KB
sha256, published bytes
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Every receipt and every verdict array the kit carries, one record each, with its own sha256 in full. The receipts are append-only: a gate that ran more than once keeps every reading, and an earlier one is numbered past rather than erased.

What is withheld is named too — every class, its own refusal mechanism and its sha, in the records under “what is withheld” above.

Thanks

Who ran this, and thanks

The texts. An authored world, in a campaign file down to its typos: a herring village on a grey bay, its residents' birth years, grudges and voice lines, and the storm of 1888 the whole town still argues over. The six sealed bundles are that world's own state, captured by the engine that runs it and sealed 2026-08-14 11:42:43 UTC — 25 sealed files re-hashed GREEN and all 6 registered bundles match their shas. The verse the older visitor asks about was written AFTER that seal, and the round checked it rather than assuming: the verse's text appears zero times in all six sealed bundles, while the word verse occurs 4 · 2 · 0 · 14 · 0 · 10 times across them — so the bundles NAME the verse and never give its words.

The judges. The 6 model families that read, every one of them through the same shelf: Google's Gemma 4 (31B) (gemma4:31b), Mistral Large 3 (mistral-large-3:675b), NVIDIA's Nemotron 3 Ultra (nemotron-3-ultra), Moonshot's Kimi K3 (kimi-k3), DeepSeek V4 Pro (deepseek-v4-pro:0813), Alibaba's Qwen 3.5 (397B) (qwen3.5:397b). One of them built a contestant: google built the local seat, the model that holds this chair in the live game, and its own chair is recused from that row — which is why that row carries one family and eight cells fewer than the others. Neither frontier arm's family holds a chair here at all. Each read a lettered sheet with no model name on it, each was recused from its own family's row, and every one of their notes publishes beside the cell it decided. One seat was asked and did not sit: Zhipu's GLM 5.3 (glm-5.3) filed NOT-CARRIED at the audition and was retired for the round (6 seats of 7 — glm-5.3 NOT-CARRIED) — it read no sheet, and it is named here because a panel of seven that answered as six should be visible in the credits and not only in the tables.

The local seat. gemma4:26b on our own hardware — the model that answers real visitors at this chair — and the ollama runtime it runs on. The posture it sat at, in the roster's own words: exactly the open call's house posture: think:false, format:"json" ACTUALLY ENFORCED, num_ctx 32768, and NO sampler fields (no temperature, no top_p, no num_predict) — one request in flight, on a 96 GB-class workstation GPU (amendment COVE-A1; the row carries no sampler cell and no output-cap cell).

The layer beneath. Python 3 and its standard library. The scoring is the open call's own scorer, copied byte for byte and re-hashed at every scoring run — sha ff0b620d…, matching the registered pin — which is what the exact same scoring method as last time means at the level that matters, the code. The roads: 2.1.263 (Claude Code) was the road to claude-fable-5-1; the OpenAI API, at the rates cited on 2026-09-05, the road to gpt-6-astra; and the ollama.com shelf the road to glm-5.3 and to every judging seat this round asked (6 seats of 7 — glm-5.3 NOT-CARRIED).

The humans. An operator read the pre-registration and co-signed it before the first call (~10:2xZ 2026-09-06 UTC), ruled on what could leave our machines, and read this page before it went out (2026-09-07 00:35:00 UTC). The adversarial reads ran on an Anthropic model — the same family that wrote this page, ran this round and sits as one of the four arms, so this reader could not be recused the way every judging seat was, and the page names that rather than call the reader independent. It read an earlier version of this page against the kit, the sealed pre-registration and the scorer's output; what it questioned and what changed are in its own receipt (2026-09-07 01:03:09 UTC). And a reader from outside this house — mistral-large-3:675b, a family that wrote none of this and judges no arm here — was handed the pre-registration itself and asked to find every choice in it that favours one arm. Its raw reply ships with the round, and every finding it raised carries a disposition in the pre-registration's own amendments. The numbers were written by the scorers; every figure above names the file and the field it came from, and the kit holds both.

The rest of the seminar

The rest of the seminar

Behind this page: A kid, an elder, and a tired parent walk into the cove, the open call, where the chair, the cove and the blind-panel-with-recusal method were built and twenty models sat the narrator's chair; and Two New Frontier Models at the Rules Desk, exhibit forty, where the same two strangers sat a sealed rules exam judged by the same seven families, and this page was promised.

The shelf holds every kit; the contact desk is hello@strata2signal.com. If you find an error this page has not already printed against itself, we would like to print that too.

Licence: CC BY 4.0 for the text and the kit; every reply, table and receipt on this page is machine-written from the round's own artifacts and human-checked.

elsewhere in the workshop

a strata→signal property · hello@strata2signal.com · say hello