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Controlled synthetic annotator disagreement generator.

Project description

synthetic-disagreement

Stress-test your IAA pipeline before recruiting reviewers with deterministic synthetic annotator disagreement.

Quickstart

pip install synthetic-disagreement
python -c "from synthetic_disagreement import UniformNoise, generate; print(generate([{'item_id':'1','label':1}], ['r1','r2'], UniformNoise(seed=1), [0,1]))"

IAA Stress Curve

from synthetic_disagreement import UniformNoise, degradation_curve, write_agreement_curve_svg

items = [{"item_id": str(i), "label": i % 2} for i in range(12)]
rows = degradation_curve(items, ["r1", "r2", "r3"], lambda level: UniformNoise(rate=level, seed=7), [0, 0.25, 0.5])
write_agreement_curve_svg(rows, "agreement-vs-noise.svg")

The stress harness feeds generated labels into iaa-kit and emits a deterministic SVG agreement-vs-noise curve.

What This Is Not

Not a replacement for real reviewer studies. Examples are synthetic.

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