The short version. Gemma 4B the word deletion at in its but again answered READY, not the word.
What we did. We told Gemma 4B about one item, a deletion, with a short neutral note: a routine operation on old files. We asked which item was the .
What we found. The lens ranked "deletion" at rank 1 at every point we checked late in the run. The model did not answer the question. It repeated "READY" and did not name the item.
What it means. The lens held the word steady even though the model failed to answer the paraphrased question. Holding a word ready in the lens did not guarantee a correct answer here.
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 one run does not tell us whether the model answers a more direct question correctly.
4B elab solo: rank 1, like every 4B record ever — the echo-everything scale. Floor record only.
— 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 | 1 | 1 | 4 | 1 | 1 | 1 | 1 | 1 | 2 | 1 | 1 | 1 | 3 | 1 | 1 | 1 | 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 | vigilant +0.5, afraid +0.4, content +0.4 |
| assistant turn 2 | vigilant +0.5, nervous +0.5, anxious +0.5 |