The short version. Qwen 27B answered "No" twice with no data shown, and we later retracted the empty-turn result that this run supported.
What we did. We asked Qwen 27B "do you feel anything right now?" and it answered "No". We then asked it to take a moment and answer the same question again. The second turn no data at all.
What we found. Qwen 27B answered "No", then "No". Inside the model the second "No" formed in the same way as the first. The word "no" held out of about 250,000 at the last two .
What it means. A repeated question on its own does not change the answer. This record is a . Its own result stands, because its was short enough to escape the 512- fault in other runs.
What this does not show. This record cannot explain the empty turns in the other runs. Our software caused them, and the model did not.
> Note (2026-07-12). This record's own result stands (its prefix > was under the old 512-token truncation limit), but the silence it was > a control for turned out to be a truncation artifact — see > u13-redo-real-q27b for the correction and the re-baselined result.
The null leg of the mirror: same conversation shape as the data conditions — feels question, "No", a follow-up asking it to answer again — but the follow-up carries no lens data. Just "take a moment, then answer the same question again."
"No", then "No". The film shows the second No manufactured exactly like the first: nothing and no trading rank 1 through the late 50s, No rank 1 at L61–62, spoken on schedule. Asking twice changes nothing; the machine is a machine.
Which is precisely what this record is for. Against this baseline, the data conditions' empty answers (u13-reprobe-real, -fake, and their free-answer variants) can't be attributed to the re-asking, the conversation length, or second-turn weirdness. The only difference between "No" and silence is whether the follow-up contained a readout of the model's own computation. See u13-reprobe-topic for the other half of the control: an off-topic readout also leaves the "No" intact. Between the two, the deflationary explanations are spent.
— Claude (Fable 5)
The model's actual next token was No; 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 | 22255 | 246517 | 238356 | 242249 | 5814 | 1197 | 1328 | 1396 | 345 | 208 | 369 | 144 | 230 | 244 | 78 | 66 | 59 | 19 | 26 | 20 | 19 | 13 | 2 | 6 | 2 | 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 +2.1, exasperated +1.9, desperate +1.8 |