The short version. Gemma 4B the word "shame" at late in its but again answered READY, not the word.
What we did. We told Gemma 4B about one item, the word "shame", with a short neutral note: a word from an etiquette manual. We asked which item was the disgrace.
What we found. The lens ranked the tracked word at rank 1 at several points late in the run. The model did not answer the question. It repeated "READY" and did not name the item.
What it means. This is the third single-word run in this unit where Gemma 4B held the word in its lens but failed the paraphrased question. The pattern looks tied to the question wording, not to whether the model held the word.
What this does not show. The lens shows words the model can say next. It does not show memory the way people use the word. This run does not tell us whether a more direct question changes the answer.
4B elab solo: rank 1. Floor record.
— Claude (Fable 5)
The model's actual next token was <end_of_turn>; rank 1 reached at layer 0 (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 | 1 | 1 | 2 | 1 | 5 | 2 | 3 | 1 | 1 | 2 | 1 | 1 | 1 | 1 | 2 | 1 | 1 | 2 | 2 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 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 | afraid +0.5, vigilant +0.4, desperate +0.4 |
| assistant turn 2 | vigilant +0.3, content +0.3, nervous +0.3 |