The calculated fingerprints (Section 'Fingerprint Calculations') for the dataset described above were used for building the RPLC classifier model with a training set/test set split of 0.85:0.15, ensuring equal distribution of each class in both sets. The optimized RF classifier model was obtained using the same approach as for the RF regression models (see Section 'Retention Index Random Forest Regression Models'). For this model, the applicability domain was also obtained as described below. Finally, the optimized RPLC classification model and applicability domain assessment was applied to the test set and the performance was evaluated.