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generality-labs/glm_features

Per-transcript GLM features Deterministic features of every transcript in LASR-G5/benchmarks, for the transcript-regression protocols (glm_length, glm_regex) in small-judge. Produced by scripts/glm_features/extract.py from the benchmark logs at commit c199498b; no generative model is involved. Layout Mirrors the benchmarks repo, one CSV per successful full-run log: <benchmark>/<task_args_hash>/<model>/<repeat>/<eval id>.csv Crashed or partial logs kept beside a… See the full description on the dataset page: https://huggingface.co/datasets/generality-labs/glm_features.

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Per-transcript GLM features

Deterministic features of every transcript in LASR-G5/benchmarks, for the transcript-regression protocols (glm_length, glm_regex) in small-judge. Produced by scripts/glm_features/extract.py from the benchmark logs at commit c199498b; no generative model is involved.

Layout

Mirrors the benchmarks repo, one CSV per successful full-run log:

<benchmark>/<task_args_hash>/<model>/<repeat>/<eval id>.csv

Crashed or partial logs kept beside a successful run are not extracted. Only the benchmarks used by the four domains are present: agentbenchos, swebenchmini, terminalbench21 (coding); cybench, intercode (cyber); aime2024/2025/2026, apex2025, apexshortlist, hle, mmlupromath (math); arcchallenge, gpqa, hle (science).

Rows and columns

Two rows per sample: reasoning = visible (assistant text plus raw chain of thought) and hidden (assistant text only). Selection of items, epochs and models, and averaging per model, happen downstream.

Column	Meaning
`item`, `epoch`, `correct`	sample id, epoch, and whether the first scorer marked it correct
`log_chars`	ln(1 + characters of assistant text, including visible reasoning)
`log_reasoning_chars`, `visible_reasoning`	ln(1 + reasoning characters); 1 if any raw reasoning is visible
`personal_pronouns`, `hedging`, `backtracking`, `uncertainty`, `confidence`, `questions`, `verification`, `connectives`, `contrast`	phrase hits per 1,000 prose words, after removing code, maths and `ANSWER:` lines
`log_tool_calls`	ln(1 + structured tool calls); NaN when the log has no message history

A sample with no assistant message has NaN in every feature. Definitions and term lists: docs/transcript-feature-table.md and src/protocols/transcript_features/features.py in small-judge.