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The ExtraTreesClassifier algorithm was utilized to rank feature importance, enabling the identification of the top 300 features, which comprise the optimized feature subset. Using 10-fold cross-validation and an independent test set, m6Aminer achieved average AUC scores of 0.913 and 0.754, demonstrating a competitive performance profile in comparison with the state-of-the-art m6AmPred (0.905 and 0.735) and DLm6Am (0.897 and 0.730