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The paper evaluates variant effect predictions for ARSA gene variants, finding that a bootcamp-trained model outperformed others and that deep learning slightly improved performance over simpler methods.

The paper introduces cost models to compare pathogenicity predictors in clinical contexts, showing no optimal predictor exists for all scenarios and highlighting the importance of rejection classifiers.