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Introduces an operating-point-aware evaluation framework for adaptive data cleaning that corrects for removal-budget confounding. Experiments on CIFAR-10 and ImageNet-100 show that apparent performance gains vanish when operating points are matched, suggesting that many improvements reflect smaller removal budgets rather than genuine corruption discrimination.