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ML-based predictions are used to inform consequential decisions about individuals. How should we use predictions (e.g., risk of heart attack) to inform downstream binary classification decisions (e.g., undergoing a medical procedure)? When the risk estimates are perfectly calibrated, the answer is well understood: a classification problem's cost structure induces an optimal treatment threshold j^⋆. In practice, however, some amount of miscalibration is unavoidable, raising a fundamentalarXiv:2203.09852v1 fatcat:y7oj4gvwxncw5cwutekbvrpyim