We performed active learning using the identical machine learning setup that we employed for building the baseline model (see Table ). The performance of the active learning approach was assessed by a 5-fold CV and with holdout data (test set). Two different methods for generating the individual CV folds were explored: a stratified splitting method, which ensures identical ratios of SoMs and non-SoMs across the individual folds, and a clustering method, which ensures that the atom environments represented in the individual folds are dissimilar (see Methods for details).