To set the decision threshold for converting probabilistic predictions into binary outputs at 0.5, we applied a weighting factor of 2.8 to the binary cross-entropy loss function. This weighting counteracts the class imbalance, helping to maximize the MCC, our primary evaluation metric, by balancing precision and recall. FAME 3R uses an empirically determined optimal decision threshold of 0.3. Interestingly, AWESOM and FAME 3R predicted identical SOMs for 27% of the molecules in the test set. For the remaining 73%, the models agreed on the SOM prediction for at least one positively predicted atom but diverged on the predictions for other such atoms. Notably, there were no cases where the models were in complete disagreement. Note that these patterns of agreement and divergence are independent of whether the predictions matched the experimentally determined SOMs.