In terms of accuracy, GAME-Net-UQ yields an MAE of 0.24 eV on a test set of 2521 data points randomly sampled from the initial dataset, 0.23 eV for intermediates and 0.26 eV for transition states (Fig. ). The performed ablation study (Supplementary Note 7) shows that labeling the edge involved in the TS improves the test MAE by 0.14 eV, while encoding the generalized coordination number in the graph nodes yields an overall MAE reduction of 0.10 eV. Data with small (high) error are reflected in small (high) uncertainty, resulting in a robust model with a 0.9% miscalibration area (Supplementary Fig. ). Small adsorbates, ferromagnetic metals, and Cd and Zn show higher error (Fig. ), but the model uncertainty for these systems is positively correlated. The sharpness of the model, representing the magnitude of its uncertainty on the test set, is 0.29 eV, while the variation coefficient, which quantifies the dispersion of the uncertainty estimates, is 0.4 (Supplementary Fig. ).