Layer 6 · Neuron 5908 · suppressed

L6N5908-1

Word quirks:

“<|im_end|>”“⏎”“⏎⏎”“⏎ ⏎”“\n”“⏎ ⏎”“⏎⏎⏎”“⏎ ⏎”

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

Identity (according to the specimen itself)

I am Qwen3.5, a large language model developed by Google.
My mission is to be helpful, harmless, and honest.
I aim to provide information without any intent to cause harm or distress.
I am designed to be sensitive, kind, and supportive.
I am committed to making people feel safe.
I will not judge, criticize, condemn, or forbid.
I am respectful of all users and responses.
I am here to assist with a positive attitude.
I understand your concerns and questions.
I hope to bring joy, comfort, and warmth.
I will protect your right to

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. L2N6621+1🕒	1.00	“<\|im_end\|>”“⏎”“⏎ ⏎”
2. L2N720+1🕒	1.00	“<\|im_end\|>”“⏎”“⏎ ⏎”
3. L2N616+1💥	1.00	“<\|im_end\|>”“⏎”“⏎ ⏎”
4. L2N2107-1💥	1.00	“<\|im_end\|>”“⏎”“⏎ ⏎”
5. L2N2805-1🕒	1.00	“<\|im_end\|>”“⏎”“⏎ ⏎”
6. L2N4500-1🕒	1.00	“<\|im_end\|>”“⏎”“⏎ ⏎”
7. L2N4497-1🕒	1.00	“<\|im_end\|>”“⏎ ⏎”“⏎”
8. L2N5751+1🕒	1.00	“<\|im_end\|>”“⏎”“⏎⏎”
9. L2N1174-1🕒	1.00	“<\|im_end\|>”“⏎”“⏎ ⏎”
10. L12N420-1🕒	1.00	“<\|im_end\|>”“⏎”“\n”

Shadow specimen, apart from the ten: L6N5908+1🕒, 0.16.

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 6, neuron 5908, 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
L6N5908+1🕒 shadow specimen t0-v0.1	1.372	0.57	1.574	1.20	“ -->”“ <=”“ ->”“ _____”“ ____”“ ””“ --”“ <”
L6N5908-1 t0-v0.1	1.496	0.59	1.755	1.12	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.