We hypothesized that our stringent metric of MPR was affected by the increase in the number of functional group predictions for a given model. To test this hypothesis, we have created synthetic models based on the accuracies of each functional group from the trained IR+MS model (see Synthetic Models in the supporting information for more details). The machine learning model outperforms these synthetic models (Figures and), indicating that increasing the number of functional groups does not decrease this metric more than what would be expected from the inclusion of additional functional groups alone. The overall conclusion of this section is encouraging as it suggests that more functional groups can be added to our model without hurting the model's ability to predict other functional groups. Values for the MPR and MF1 scores for the new functional group definitions are given in Tables and.