results/README.md

Results

Raw predictions for the table in the dataset card. Full test split, zero-shot, temperature 0, prompt v1, run 2026-07-11 through OpenRouter. One directory per model, one JSONL per config; scores.json holds every metric.

Each prediction row records the model, prompt version, reasoning setting, and finish reason, so the files describe their own runs. Reasoning settings: gpt-oss-120b ran at effort low with max_tokens 4096 (at 1024 it spent the budget thinking and answered nothing on 10% of notes_to_rn); Claude Sonnet 5, DeepSeek-V3.2, and Kimi-K2.5 ran with reasoning disabled; Qwen3-235B-Instruct and Llama-3.3-70B do not reason.

reasoning/ holds the reasoning-on comparison runs: same prompts, reasoning effort high, max_tokens 8192, on fixed subsets of test (first 200 records per config; 150 for Kimi-K2.5, 100 for Claude Sonnet 5). Score them against the same records from the parent directories for the paired comparison; reasoning/scores.json has both sides precomputed.

Reproduce a run:

python eval/run_model.py --config notes_to_rn --split test \
  --model openai/gpt-oss-120b --reasoning low --max-tokens 4096 \
  --base-url https://openrouter.ai/api/v1 --api-key $OPENROUTER_API_KEY \
  --out preds.jsonl
python eval/score.py preds.jsonl --config notes_to_rn --split test