After introducing the target values and feature vectors, we now divide the MCA and MAA datasets into training and held-out test sets using a binned split approach, with 85 % of the data allocated for training and 15 % reserved for testing. Specifically, this results in a training and held-out test set of 553,228 and 97,629 atomic sites for the MCA model and 454,001 and 80,118 atomic sites for the MAA model. The binned split ensures that the distribution of target values as well as the partitioning of functional groups is consistent across both sets as seen in the Supporting Information.