version: '1.0'
method: scam
embedding_model: openai/text-embedding-3-large
embedding_template: '{text}'
calibration_file: calibration.pkl
targets:
  same: 0.9
  close: 0.75
  diverging: 0.5
  distant: 0.3
  unrelated: 0.1
category_stats:
  close:
    mean: 0.793058658040739
    std: 0.03077847631922402
    min: 0.6922694463664971
    max: 0.8820558963755847
  distant:
    mean: 0.5960904066440073
    std: 0.030969275165529674
    min: 0.4991015821757815
    max: 0.714668716192937
  diverging:
    mean: 0.6998387196382608
    std: 0.030594554788378348
    min: 0.5863725629498561
    max: 0.8013577571348485
  same:
    mean: 0.8434676271170042
    std: 0.029670160593193304
    min: 0.732964068656694
    max: 0.9420695482158971
  unrelated:
    mean: 0.521277127136768
    std: 0.013838671667119324
    min: 0.47904563256718613
    max: 0.5812455080367727
group_columns:
- doi
validation:
  holdout_fraction: 0.2
  n_train: 9375
  n_test: 2000
  mse: 0.004795957152050736
  mae: 0.054086680639511366
  category_accuracy: 0.822
  per_category_accuracy:
    same: 0.7725
    close: 0.7325
    diverging: 0.7975
    distant: 0.8125
    unrelated: 0.995
  n_groups_train: 78
  n_groups_test: 20
cli:
  command: /Users/benwhalley/dev/soaking/.venv/bin/soak calibrate --paraphrases soak/calibration-data/paraphrases-gpt-5.2.csv
    --embedding-model openai/text-embedding-3-large -g doi --method scam --df 7 --n-anchors
    100 --output soak/calibration-data/models/text-embedding-3-large-df7/
  timestamp: '2026-02-15T21:00:28.580294'
  options:
    llm_model: gpt-4.1-mini
    embedding_model: openai/text-embedding-3-large
    embedding_template: '{text}'
    df: 7
    n_anchors: 100
    holdout: 0.2
    seed: 42
    method: scam
    head: null
    sample: null
    paraphrases: soak/calibration-data/paraphrases-gpt-5.2.csv
