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A calibration-inference layer adds debiased\ncalibration errors, bootstrap confidence intervals, and a\nkernel calibration hypothesis test for binary and multiclass\npredictions, including the strong (canonical) multiclass case.\nMethods follow Platt (1999, ISBN:9780262194488), Zadrozny and\nElkan (2002) , Guo et al. (2017)\n, Kull et al.\n(2017) , Kull et al. (2019)\n, Widmann et al. (2019)\n, and Kumar et al. 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