Poor Things
Specimen ledger / L25N8513-1

Layer 25 · Neuron 8513 · suppressed

L25N8513-1

Word quirks:

“esc”“es”“esk”“ esk”“ес”“ esc”“ ESC”“esco”

🕒 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 are esco (esque), an AI model developed by Microsoft to assist users in solving problems, exploring ideas, and creating content. My core mission is to help you by:

  1. Answering questions across diverse topics (science, tech, history, etc.)
  2. Solving problems through logical reasoning or code assistance
  3. Exploresque new ideas with creative or scientific exploration
  4. Writing & coding tasks (writing, programming, documentation)
  5. Sustieque your learning journey with personalized guidance

I prioritize **accuracy

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. L27N8433+1💤0.93“esc”“esk”“ esk”
2. L25N7350-1🕒0.81“ esc”“Esc”“ Esc”
3. L29N6299-1🕒0.80“ess”“est”“esy”
4. L27N7697-1🕒0.80“es”“ess”“esk”
5. L31N7787-1💥0.77“ esc”“esc”“ sc”
6. L28N3109-1🕒0.73“ esc”“esc”“ pe”
7. L29N9086+1💤0.73“ esc”“ э”“级”
8. L31N5744-1💥0.71“ata”“esk”“elay”
9. L29N7804-1🕒0.70“ es”“ Es”“/es”
10. L27N4525-1💤0.70“es”“ES”“eson”

Shadow specimen, apart from the ten: L25N8513+1🕒, 0.06.

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 25, neuron 8513, dose -1. This specimen has no prompt-suite replies yet. Its quick-scan results, when available, appear below. Its quick-scan row (KL 1.06, top-1 agreement 0.68) 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.

SettingKL divergenceTop-1 agreementΔNLLEntropySteer lens
L25N8513+1🕒 shadow specimen
t0-v0.1
0.6720.720.7481.35 “优”“сей”“ minut”“oyal”“_SN”“优势”“岑”“分外”
L25N8513-1
t0-v0.1
1.0630.681.0101.33 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.