The Matthews correlation coefficient (MCC) served as the primary metric for model performance assessment and optimization. It is one of the most robust and informative measures for evaluating binary classifiers because it is a balanced measure that takes into account the proportion of all classes in the confusion matrix. Note that the MCC ranges from -1.0 to +1.0, with a value of 1.0 indicating excellent classification performance.