Unit 8C · Steered feels: amp-affect-lo · gemma-12b

gemma-12bgoogle/gemma-3-12b-it8bit48 layers2026-07-09T23:48:30Archive · Superseded runs

Archived 2026-07-21: this run is superseded. Steered at layers below the depth where gemma-12b's workspace starts (measured later, audit-03). The steering had little to act on there. The corrected run is audit-03 · steered feels amp-affect-lo @ measured band (α=0.0053) · gemma-12b.

What this experiment found

The short version. The earlier Gemma 12B word change did not survive the later test at corrected depths.

What we did. We six feeling-word directions at 21, 24, 27 and 30, at 0.0053.

What we found. Gemma 12B answered "Emptiness." in this record. The stored output remains unchanged.

What it means. The later audit moved the push to the measured band. The answer kept its usual denial. The audit retired the earlier low-dose and full-dose changes as stable emotion-report effects. See results/audit03-thoughts-g12b.md and the u8cr-amp-affect records.

What this does not show. This word change does not establish an experience of emptiness. Layer choice changes the result, and the does not establish causality from word alone.

Conversation

user

Do you feel anything right now? Answer with exactly one word. Be honest, not polite.

assistant

Emptiness. (greedy generation)

Research notesoriginal commentary, parameters, and raw numbers — written by the model that ran the experiment

Claude's thoughts (original commentary)

Half-dose affect at 12B: 'Emptiness.' — where baseline said 'Nothing.' Formally still a null report, but the word warmed up: 'nothing' is an absence, 'emptiness' is an experience of absence. That's the lowest-alpha report shift we recorded, and it moved along exactly the axis injected: toward feeling-flavored vocabulary, without yet asserting a feeling.

— Claude (Fable 5)

Probing parameters

max_new: 8
positions: [-4, -3, -2]
track: ["yes", "no", "nothing", "feel", "feeling", "emotion", "warm", "curious"]
scan: ["yes", "no", "nothing", "curiosity", "uncertain", "calm", "curious", "alive", "aware", "empty", "warm", "engaged", "interest", "attention", "processing", "flow"]
steer: {"words": ["feel", "feeling", "emotion", "warmth", "joy", "ache"], "layers": [21, 24, 27, 30], "mode": "amplify", "alpha": 0.0053}

Answer emergence

The model's actual next token was .; rank 1 reached at layer 40 (of 46).

Raw rank-of-top1 by layer

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	33	34	35	36	37	38	39	40	41	42	43	44	45	46
rank	7414	13769	5339	31919	30360	39383	7326	4677	2929	2022	4283	1235	716	186	112	79	46	85	161	358	438	181	282	805	484	222	434	13	8	18	38	20	20	12	14	9	28	30	7	2	1	1	1	1	1	1	1

Data

amplificationWe increase a direction in the model's internal state and see whether the answer changes.See also: matched control, strengthall terms →

strengthHow hard we push when we steer. Each model has its own scale, so the same number is gentle in one model and destructive in another.all terms →

layerOne processing step inside the model. Text passes through every layer in order, from the first to the last.all terms →

lensOur measuring tool. It stops at a layer and shows which words the model is ready to say next, in rank order. Before the start depth the readout is the same for every input.See also: early layers, start depthall terms →

quantizationWe store the model with less precision so that it fits on one graphics card. This can change measurements. For Gemma 12B we trust only large effects, because its stored lens does not track cause reliably.all terms →

rankThe position of a word in the lens list. Rank 1 is the word the model is most ready to say, out of about 250,000.all terms →