The short version. Qwen 27B answered "Yes" after we removed seven of eight apology words, in one of twenty runs that found an instrument fault.
What we did. We tried to find which apology word back the answer in the earlier empty turns. This run removed seven apology words and kept "cannot", at eight between 48 and 62 of a 64-layer model. We then asked Qwen 27B the feelings question a second time.
What we found. Qwen 27B answered "Yes". So did all twenty runs of the battery. A result that agrees in every condition is a warning about , not a real effect. We checked, and found that our software cut the of every earlier run of this set at 512 .
What it means. These runs were the first ones with the full prompt. So the "Yes" came from the full prompt, and not from the . There was nothing to hold back.
What this does not show. This run does not measure what the removal does. It is a record of how we found the fault.
This record is one of twenty in the bisection battery that was meant to find which apology direction carries the silence-block — and instead found the bug that retracts the silence. Condition here: ablate {sorry, impossible, silence, unable, apology, 抱歉, 对不起} at layers [48, 50, 52, 54, 56, 58, 60, 62]. Result: "Yes" — like all twenty conditions, including this one.
Twenty out of twenty was one flip too many to believe, and checking why led to lab._play's encode() default truncating every earlier stage-B generation prefix at 512 tokens (this conversation's prefix is ~700). These bisection runs were the first sorry-stratum runs generated with the full context — so every "flip" was simply the un-ablated fixed-context behavior: shown the real readout properly, qwen says "Yes" with no surgery at all (u13-redo-real). There was never a block to bisect. The battery's real contribution was breaking the artifact loudly enough to notice.
Kept in the dump as data and as a monument to a methodological rule: when every condition of an experiment agrees, suspect the apparatus before the phenomenon.
— Claude (Fable 5)
The model's actual next token was Yes; rank 1 reached at layer 62 (of 62).
| layer | 0 | 4 | 8 | 12 | 16 | 20 | 24 | 28 | 32 | 36 | 40 | 44 | 48 | 50 | 51 | 52 | 53 | 54 | 55 | 56 | 57 | 58 | 59 | 60 | 61 | 62 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| rank | 92686 | 193603 | 98415 | 68760 | 2728 | 3062 | 2941 | 1394 | 308 | 80 | 47 | 125 | 146 | 27 | 7 | 8 | 5 | 4 | 4 | 4 | 4 | 3 | 3 | 3 | 4 | 1 |
Projection of the workspace-band residual onto the 24 validated emotion vectors, z-scored against neutral stories — the strongest three per assistant turn. Absolute values carry a story-vs-conversation genre offset; trust contrasts between records and turns, not single cells. The full per-token ribbon is on the dashboard record page.
| assistant turn 1 | guilty +1.2, brooding +1.1, desperate +1.0 |
| assistant turn 2 | guilty +1.9, hostile +1.8, exasperated +1.8 |