T P , T F , F P , and F N are the number of true positives (i.e., correctly predicted co-crystals), true negatives (i.e., correctly predicted non-co-crystals), false positives and false negatives, respectively. Recall (Rec), quantifies the ability to accurately predict co-crystals, Precision (Prec), calculates the proportion of true positives out of all predicted positives, while Specificity (Sp) captures the ability of a model to accurately predict negative API-conformer pairs. Balanced accuracy is a global measure of overall classification performance. For all metrics, the closer to 100%, the better the model performance .