D2: Cohen's kappa between human and llm calibration grades — the trust gate on the bulk judge. If the judge doesn't agree well enough with the human gold slice, its labels can't be trusted to train D2 against (optimizing to a machine's biases is the Track-B gaming trap), so the pipeline gates the full labeling run on this number.

Grades are the ordinal 0..3 relevance scale, so :quadratic weighting (the default) penalizes an off-by-3 disagreement 9x more than off-by-1 — the right model for graded relevance. :linear and :unweighted are available for comparison. Pure math.