The performance of the models increased steeply as more atoms were selected and used for training (Figure ). After approximately 6000 iterations already (meaning the use of just 6000 atoms, or 25%, of the data available for model building), the MCC for the validation sets approached values of 0.50 and better, with maxima recorded for individual iterations in the range of 0.50 to 0.55. The standard deviations for the MCC maxima during the five repeats of active learning were just 0.01 when using stratified random splitting to generate the five data folds, and 0.02 when using the clustering approach. Because the stratified split method showed better stability during the active learning process, further discussion will focus on the results obtained with this data splitting method.