Energy descriptors play a major role in the model's prediction, and the geometry-based new descriptors, while playing a more secondary role, are key in evaluating the gaps between the low-pressure case with the ambient-pressure one that we are interested in. To dig deeper into the mechanisms that allow the model to predict the selectivity with a very good accuracy -the RMSE and MAE on the test set's selectivity being respectively 2.5 and 1.1 -we are now going to look into the SHAP dependence plots of each interesting descriptor that plots the contribution to the predicted value as a function of the actual descriptor value.