From Figure and the analysis presented in Figure , it is expected that the interpretations from SHAP in HCat-GNet are related to the disposition of atoms in space resulting from the chiral carbons in the structure. For the case of ligand (R,R)-L3, the addition is done in the top face, while for (S,S)-L1 and (S,S)-L2 is done in the bottom face. Remarkably, the SHAP analysis demonstrates that HCat-GNet is effectively learning that the main drivers of the facial selectivity in the reaction are the asymmetric carbons in the structure. As shown in Figure , the asymmetric carbons in the structure are found to contribute positively to the outcome variable (larger %topA), while from Figure and 8c the asymmetric carbons are found to contribute negatively (lower %topA). This is reassuring, as it indicates that the model is being able to learn the correlation between the configuration of the ligands and the selectivity outcome, and that the predictions done make sense from a chemical perspective. Due to the limited diversity of ligands in our dataset, no further information, such as the impact of substituents in the structure of the ligand, is available.