The overall performance of the various EGAT architectures was tested by predicting the activation energy of the 12.3k reactions in the RGD1 testing split (Fig. ). There is remarkably little variation across the different EGAT architectures; all models show uniformly low mean absolute prediction errors (MAE) of ∼4 kcal/mol. None of the models show a significant systematic bias based on the negligible mean signed errors (Fig. ). The G→ E a model that doesn't use the ∆H r information intuitively shows the largest MAE, but only performs ∼0.5 kcal/mol worse on average than G→ BEP, the best EGAT model. The models were tested as ensembles of five independently trained models of each class. The standard deviation in the mean testing split performance of the individual models comprising the ensemble provides an estimate of the testing performance uncertainty (error bars in Fig. ). The mean performance uncertainty is also within ∼0.5 kcal/mol in all cases.