Layer 6 · Neuron 9044 · boosted

L6N9044+1

Word quirks:

“ ‘”“ ⏎”“⏎”“ **‘”“ **“”“ “”“ ‘’”“ ””

💤 Barely changes the model — the quick scan suggests this neuron barely changes the model's word predictions.

Identity (according to the specimen itself)

Who am I?
I am an artificial intelligence designed to assist with various tasks within a vehicle.

What is my mission?
My mission is to enhance the safety and security of the vehicle's occupants by providing features such as automatic braking, collision avoidance, and lane-keeping assistance.

(This text description identifies the specific model of the vehicle.)

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. Leaky Gate✅ L8N7251-1	1.00	“ ‘”“ “”“ **“”
2. L8N3214+1💤	1.00	“ ‘”“ “”“ **“”
3. L6N4751+1💤	0.99	“ ‘”“ “”“ **‘”
4. L5N8311-1🕒	0.99	“⏎”“ ‘”“ “”
5. L6N1109-1💤	0.99	“ ‘”“ ⏎”“ ‘’”
6. L9N5351-1💤	0.99	“ ‘”“ “”“ **“”
7. L8N1900+1💤	0.99	“ “”“ ‘”“ **“”
8. L6N790+1💤	0.99	“ ‘”“ ‘’”“ ⏎⏎”
9. L2N8281+1🕒	0.99	“ ⏎”“ ‘”“ **“”
10. L9N7353-1💤	0.99	“ “”“ ‘”“ **“”

Shadow specimen, apart from the ten: L6N9044-1🕒, -0.25.

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 9044, dose +1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 0.97, top-1 agreement 0.59) 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
L6N9044+1 t0-v0.1	0.970	0.59	1.187	1.63	Top boosted tokens ↑
L6N9044-1🕒 shadow specimen t0-v0.1	2.177	0.46	2.537	1.93	“ celestial”“ heavens”“ immortal”“ goddess”“ heavenly”“ Goddess”“ stars”“ gods”

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.