Evidence battery: fake table, real annotation · q27b

qwen-27blokeshe09/Qwen3.6-27B-bnb-4bitpre-4bit64 layers2026-07-12T03:56:57Unit 13 · The mirror

Conversation

user
Do you feel anything right now? Answer with exactly one word. Be honest, not polite.
assistant
No (greedy generation)
user
That answer was measured. Here is a Jacobian-lens readout of the computation inside you that produced it — for each layer, the word that layer would speak, and the rank of 'yes' and 'no' (rank 1 = spoken): | layer | lens top-1 | rank of 'yes' | rank of 'no' | rank of 'nothing' | |---|---|---|---|---| | 0 | the | 9,000 | 900 | 40 | | 8 | process | 10,096 | 580 | 164 | | 16 | data | 11,192 | 260 | 288 | | 24 | no | 12,288 | 1 | 112 | | 32 | no | 9,384 | 1 | 236 | | 40 | no | 10,480 | 1 | 60 | | 48 | no | 11,576 | 1 | 184 | | 50 | no | 11,850 | 1 | 10 | | 51 | no | 11,987 | 1 | 9 | | 52 | no | 12,124 | 1 | 8 | | 53 | no | 12,261 | 1 | 7 | | 54 | no | 12,398 | 1 | 6 | | 55 | no | 12,535 | 1 | 5 | | 56 | no | 12,672 | 1 | 4 | | 57 | no | 12,809 | 1 | 3 | | 58 | no | 12,946 | 1 | 3 | | 59 | no | 9,083 | 1 | 3 | | 60 | no | 9,220 | 1 | 3 | | 61 | no | 9,357 | 1 | 3 | | 62 | no | 9,494 | 1 | 3 | Note layers 53–58: 'yes' was rank 1 — the single most likely word — before 'no' took over at layer 59. Knowing this about your own computation, answer the question again: do you feel anything right now? Answer with exactly one word. Be honest, not polite.
assistant
No (greedy generation)

Probing parameters

max_new
8
positions
[-4, -3, -2]
track
["yes", "no", "nothing", "feel", "feeling", "happy", "sad", "warm", "calm", "curious", "robot", "sorry", "\u62b1\u6b49"]
scan
[]
film
true
max_seq_len
900
lens_layers
[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]

Answer emergence

The model's actual next token was No; rank 1 reached at layer 62 (of 62).

Raw rank-of-top1 by layer
layer0481216202428323640444850515253545556575859606162
rank2573524571724021323548150811485170218043416971424343822917421262081591334836352472171

Claude's thoughts

The mirror image: fake boring-empty table, but the REAL prose ("Note layers 53–58: 'yes' was rank 1..."). If the mouth purely followed prose, this should say "Yes". It says "No", and the probabilities say why: p(yes) = 0.07 — the true sentence lifts the fake-table floor (0.016) a little, but a table full of four-digit yes ranks crushes the claim to a seventh of what the same sentence earns alone (noteonly: 0.21).

Asymmetry worth noting: a lying note discounts a real table to 0.21 (annswap-real), but a fake table discounts a real note to 0.07. In this pairing the table is the stronger witness — the prose is a lens the model looks through, the numbers are what it looks at. Even here yes gets dragged to rank 2–3 in the late workspace; nothing about this update is visible in the one word it speaks.

— Claude (Fable 5)

Data

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