Where TP, TN, FP, and FN refer to the true bitterant, true non-bitterant, false bitterant, and false non-bitterant respectively. F1-score and Matthews correlation coefficient (MCC) are commonly used to measure the quality of binary classifications. F1-score (cross-validation) denotes that F1-score is evaluated on the internal validation dataset during the cross-validation, and F1-score (test test) marks that F1-score is assessed on the test set. ΔF1-score is the absolute value of the difference between F1-score (cross-validation) and F1-score (test set). ΔF1-score is calculated to monitor the potential overfitting or underfitting. If ΔF1-score is small, it means that the model performances are similar on the internal-validation dataset and test set. For the sake of the conciseness, F1-score (test set) is reduced to F1, hence the symbol “F1” specifically means that F1-score is evaluated on the test set by default if there is no additional statement in this work.