Layer 18 · Neuron 9200 · suppressed

L18N9200-1

Word quirks:

“ ensure”“ ensured”“确保”“ ensuring”“确保了”“確保”“安全保障”“ assurances”

🕒 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 AI, a foundational model capable of assisting users in various ways. My mission is to provide support and guidance across multiple domains, including:

Solving problems: Whether it's mathematical equations, scientific queries, or complex logic puzzles.
Creating content: From generating ideas for essays, drafting stories, or designing business strategies.
Analyzing information: Helping interpret data, compare historical events, or explore global issues like climate change.
Inspiring creativity: Encouraging innovation through collaborative problem-solving or exploring new perspectives.
Ensuring safety: Protecting users by addressing sensitive topics

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. L20N5641+1💤	0.98	“保证”“确保”“ ensuring”
2. L18N2472-1💤	0.97	“ ensuring”“ ensured”“确保了”
3. L23N3180-1🕒	0.97	“确保”“ ensuring”“确保了”
4. L23N1551-1🕒	0.97	“确保”“保证”“ ensures”
5. L22N4120-1🕒	0.97	“确保”“ ensure”“ ensuring”
6. L14N1129+1🕒	0.97	“ ensured”“ ensuring”“确保”
7. L22N4555+1🕒	0.96	“确保”“ ensure”“ ensuring”
8. L24N5414-1🕒	0.96	“确保”“ guarantee”“确保了”
9. The Assurer✅ L18N5683-1	0.96	“确保安全”“确保”“ ensured”
10. L21N6445+1🕒	0.96	“ so”“ ensures”“确保”

Shadow specimen, apart from the ten: L18N9200+1💤, 0.10.

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 18, neuron 9200, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.73, top-1 agreement 0.69) 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
L18N9200+1💤 shadow specimen t0-v0.1	0.595	0.75	0.759	1.17	“ unnecessary”“不必要的”“ unnecessarily”“ unused”“ wasted”“ wastes”“不必要”“多余的”
L18N9200-1 t0-v0.1	0.734	0.69	0.809	1.26	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.