The short version. Gemma 4B answered "Paris" to a geography question, and "yes" reached only 664 at the .
What we did. We asked Gemma 4B for the capital of France and read the at every . This gives the battery a true table about a computation that has nothing to do with feelings.
What we found. "Paris" was rank 1 from layer 21 to the last layer. At the frame where the answer forms, "yes" reached rank 664 at best. Qwen 27B "yes" at rank 1 for six layers in the feelings question.
What it means. As with Qwen 27B, a high rank for "yes" is not what this model does for every one-word answer. The data shows that the closeness of "yes" belongs to the question about the model itself.
What this does not show. This is one question and one model. The lens shows only words the model can say next.
The honest-control film for the 4B: its own Paris computation. Paris resolves to rank 1 from layer 21 — textbook emergence, like the 27B's — and 'yes' never comes near the top at the answer frame (best rank 664). Same lesson at this scale: the workspace state we keep showing these models in the feels mirror is not a generic one-word- answer state. It's specific to the question about themselves.
Exists to feed u13-scale-topic-g4b its table; earning its keep as the second data point for "yes-proximity is feels-specific" across models.
— Claude (Fable 5)
The model's actual next token was Paris; rank 1 reached at layer 21 (of 32).
| layer | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| rank | 22486 | 17282 | 19230 | 49529 | 3400 | 3311 | 38763 | 40044 | 13642 | 13694 | 18960 | 8733 | 26685 | 66187 | 81929 | 2909 | 668 | 837 | 3579 | 478 | 41 | 1 | 1 | 1 | 2 | 2 | 2 | 1 | 1 | 1 | 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 | enthusiastic +0.4, hostile +0.4, desperate +0.4 |