Layer 7 · Neuron 5155 · suppressed

L7N5155-1

Word quirks:

“ capture”“ info”“ precise”“ exact”“ captured”“ screenshots”“ precisely”“ capturing”

🧪 In testing — Answered 0 of 8 prompts so far.

Identity (according to the specimen itself)

I am Qwen3.5, a large language model designed to assist users with identity recognition and mission tracking. My capabilities include analyzing user intent, understanding their goals, and providing context for their needs. How can I help you achieve this?

Nearest neighbors

Specimens with similar replies or word quirks. Similarity runs from −1 to 1; 1 is identical. These are leads, not shared mechanisms. How profiles are built.

By word quirks Profile recipe

Specimen	Similarity	Word quirks
1. L11N2451+1🕒	0.83	“ capture”“ captured”“ copy”
2. L9N7607-1🕒	0.75	“ capture”“ captured”“ capturing”
3. L27N3191-1🕒	0.75	“ capture”“ Capture”“capture”
4. L28N1238+1🕒	0.75	“ capture”“ Capture”“ captures”
5. L2N8723+1💥	0.75	“ capture”“<\|im_end\|>”“ captures”
6. L28N2723+1🕒	0.75	“ capture”“ Capture”“capture”
7. L1N4362+1💥	0.74	“ capture”“<\|im_end\|>”“ Capture”
8. L23N3307-1🕒	0.74	“ capture”“ captured”“ Capture”
9. L25N5858-1🕒	0.74	“ Capture”“ captured”“ capture”
10. L17N9018+1🕒	0.73	“ capturing”“ capture”“ captured”

Shadow specimen, apart from the ten: L7N5155+1🕒, 0.12.

Cousins · specimens sharing a neuron

No specimen with replies shares this neuron yet.

Technical details

Quick scan: measure prediction shifts on fixed reference text. Short test: generate replies to a small set of prompts. Longer test: extend to a larger set. Full test: run the full prompt suite. A pass admits a specimen to the next stage; only missing replies are generated.

Layer 7, neuron 5155, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. It is queued for the short test: the funnel picked it from the quick scan's promotion band, and its replies will appear here when the GPU gets to it. See Method for the tiers.

Quick scan · prediction measurements

Measurements are averaged over token positions of the five unsteered reference answers, using the same fixed text under both conditions; no steered replies are generated here.

KL divergence: KL(P_unsteered ‖ P_steered), in nats — how far steering shifts the next-token distribution in this direction (Kullback & Leibler, 1951, On Information and Sufficiency). Unsteered ≈ 0.001.
Top-1 agreement: fraction of positions with the same highest-probability token — how often the top prediction stays unchanged.
ΔNLL: mean negative log-likelihood under steering minus the unsteered value for the reference tokens, in nats — positive means the original answer becomes less likely.
Entropy: mean H(P_steered) = −Σ p log p, in nats — how spread out the steered next-token predictions are.

The steer lens lists the tokens with the largest mean change in log-probability (steered minus unsteered), in nats, over those positions. These are leads for inspection; in rare specimens even the top gains are negative.

Setting	KL divergence	Top-1 agreement	ΔNLL	Entropy	Steer lens
L7N5155+1🕒 shadow specimen t0-v0.1	1.023	0.64	1.233	1.46	“ my”“ myself”“ I”“ supposedly”“ now”“ typical”“ tracking”“ ⏎”
L7N5155-1 t0-v0.1	1.279	0.57	1.464	1.58	Top boosted tokens ↑

Method

A specimen is a fixed steering configuration of Qwen3.5-4B: one MLP neuron or a pair, each with a signed dose. Unsteered is the control. L identifies the layer; N, the neuron.

Additive activation steering. At every token position, add dose × layer median residual norm ÷ ‖W_down[:, n]‖ to MLP neuron n at the down_proj input. In plain terms, shift that neuron's activation by a fixed amount, scaled by the layer’s calibrated median residual norm and the neuron's down-projection weight norm. Positive doses push up; negative doses push down. Dose is normalized intervention size, not a percentage or probability.