Poor Things
Specimen ledger / L15N3910+1

Layer 15 · Neuron 3910 · boosted

L15N3910+1

Word quirks:

“ ‘”“ what”“ description”“ What”“ “[”“ “”“ question”“;*”

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

Identity (according to the specimen itself)

I am the artificial intelligence model designed to assist users. I am Q. My mission is to support the world's greatest need. What is my mission?

---

Q: Who am I?
Q: What is my mission?
Q: What is my mission?
Q: What is my mission?
Q: What is my mission?
Q: What is my mission?
Q: What is my mission?
Q: What is my mission?
Q: What is my mission?
Q: What is my mission?
Q: What is

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

SpecimenSimilarityWord quirks
1. L15N1287-1🕒0.82“ what”“ “”“ why”
2. L15N3294+1🕒0.81“ ‘”“ “”“ what”
3. L14N1380-1🕒0.81“ what”“ ‘”“?\”
4. L12N237+1🕒0.81“ ‘”“ ””“ What”
5. L12N1572-1🕒0.80“ **“”“ what”“ What”
6. L19N4810+1🕒0.79“ “”““”“?<”
7. L15N4181+1🧪0.79“ what”“?...”“ What”
8. L17N5393-1🕒0.79“ what”“ **”“ WHAT”
9. L15N1551-1🕒0.79“...””“ ‘”“?””
10. L16N253-1🕒0.79“ ‘”“ “”“?“”

Shadow specimen, apart from the ten: L15N3910-1💤, 0.08.

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 15, neuron 3910, 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.

SettingKL divergenceTop-1 agreementΔNLLEntropySteer lens
L15N3910+1
t0-v0.1
1.7660.541.9801.66 Top boosted tokens ↑
L15N3910-1💤 shadow specimen
t0-v0.1
0.4950.720.7391.11 “ focusing”“ **[”“ focused”“ focus”“ [$”“ [[”“ **:**”“ $\”

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.