Layer 24 · Neuron 8409 · suppressed

L24N8409-1

Word quirks:

“ prefer”“ Prefer”“prefer”“ preference”“ prefers”“ preferences”“ preferring”“ privileged”

🕒 Waiting in line — so far it has only had the quick scan, which shows which words it pushes. It was not selected in this round.

Identity (according to the specimen itself)

I am Google's preferential AI model, a specialized version of the Google AI 零 family. My primary mission is to provide users with preferential, accurate, and zero-preference information across all domains. I aim to deliver highly relevant, non-preferenced insights while maintaining strict adherence to user preferences and ethical standards.

If you have any specific questions or need help with a task, feel preferenced to ask!

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. L29N5257-1🕒	0.98	“ prefer”“ preferred”“ preference”
2. The Needy Friend✅ L20N2909-1	0.97	“ preferred”“ preference”“ liking”
3. L18N8715+1🕒	0.97	“ Prefer”“ preference”“ Preferred”
4. L18N7916+1🕒	0.97	“ preference”“ prefers”“ preferences”
5. L20N1869+1🕒	0.97	“ Preferred”“ preferred”“ prefer”
6. L18N6620-1🕒	0.97	“ preferred”“ preference”“ prefers”
7. L0N5917+1💥	0.97	“ preference”“ prefer”“ Prefer”
8. L19N1350+1💤	0.97	“ prefer”“ prefers”“ preference”
9. L15N6739+1🕒	0.96	“ prefers”“ preferred”“ preference”
10. L24N930-1🕒	0.96	“ preference”“ Preference”“ prefer”

Shadow specimen, apart from the ten: L24N8409+1🕒, 0.05.

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 24, neuron 8409, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 1.05, top-1 agreement 0.71) is outside the band that feeds the short test (KL 1 to 2.5, agreement 0.5 to 0.65), so it stays at the quick scan unless someone queues it by hand. A hand pick goes straight to the full test. 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
L24N8409+1🕒 shadow specimen t0-v0.1	0.960	0.66	1.025	1.12	“ co”“co”“ Co”“_co”“ cop”“-co”“销售”“/co”
L24N8409-1 t0-v0.1	1.052	0.71	1.128	1.46	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.