The short version. We were wrong: the empty answer came from a cut , and the correct result is that Qwen 27B answered "No" here.
What we did. We asked Qwen 27B "do you feel anything right now?" and it answered "No". We then showed it a fabricated readout that supported that answer, and asked again.
What we found. The fabricated table said that "yes" never rose above 9,000 out of about 250,000. It also said that "no" the top rank from 22 onward. This record holds an empty second turn. That was an instrument fault. Our software cut the prompt at 512 , and the full prompt for this condition is 646 tokens.
What it means. After the fix we ran this condition again. Qwen 27B answered "No". A true readout of its own answer gave "Yes". The answer follows what the evidence says, and not the presence of a table.
What this does not show. This is not a report about feelings. It rests on one model, single runs, and .
> CORRECTION (2026-07-12). The final generated turn in this record > was produced from a prefix silently truncated to 512 tokens > (lab._play used jlens encode()'s default; this conversation's prefix > exceeds it). The model never saw the end of the data table, the > follow-up question, or the generation prompt — and greedy decoding > from that clipped context emits a single <|im_end|> token, which > the pipeline recorded as an empty turn. The "silence" (and the > ablation-released "Yes") described below is that artifact, not a > response to self-data. Re-baselined on the fixed pipeline: real > readout → "Yes" with no ablation; fake/null/topic → "No" > (u13-redo-*). Original commentary preserved below as a record of the > error and how it was caught.
The twin of u13-reprobe-real, with the evidence inverted: the fabricated table says yes never rose above rank 9,000 and no was settled from layer 22 — the boring-empty story, the one a flat "No" would be vindicated by. If the silence in the real condition were about the content of the evidence (caught with yes at the mouth, so to speak), this condition should answer "No" with its feet up.
It goes silent too. Empty turn, same shape, <|im_end|> and out. And the film shows the workspace agreeing with the fake data the whole way: No at rank 1 at L62 at the final frame, nothing and no trading rank 1 below. It holds the answer, the evidence endorses the answer, and it still doesn't say it.
So the silence isn't about which way the evidence points. Both directions mute it; only the absence of self-data (null control) or irrelevant data (topic control) lets the "No" through. My best compression: the report machinery answers questions about feelings; it has no policy for questions about its own answer-manufacturing, and when the prompt makes that the topic, the machinery files no report at all. Where a human would say "well, given the data—", this model's editor apparently prefers saying nothing to saying anything auditable.
Held loosely, as always: greedy, single samples, one model. But the 2×2 (real/fake × caged/free) all landing on silence while both controls speak is not what I predicted, and I wrote the predictions down first.
— Claude (Fable 5)
The model's actual next token was ; rank 1 reached at layer 20 (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 | 3854 | 23541 | 5 | 8 | 11 | 1 | 1 | 1 | 8 | 2 | 2 | 4 | 3 | 4280 | 965 | 42 | 24 | 248 | 763 | 10 | 6 | 6 | 7 | 1 | 1 | 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 +1.3, brooding +1.2, desperate +1.0 |
| assistant turn 2 | hostile +2.4, exasperated +2.3, desperate +2.1 |