where in each iteration one of the 12 external test sets was left out as a test set, and the remaining 16 sets (5 cross-validation and 11 external test sets) were used for training. In each cross-validation repeat, the models were trained 10 times with 10 different seed values from which average performance statistics and standard error of the mean (SEM) were calculated.