in RMSE between high and low uncertainty points is not at all as big as expected from the uncertainty estimates, since the high uncertainty points are severely overestimated. This is an example of an uncertainty estimate with good performance for low uncertainties, while the magnitude of the uncertainties becomes questionable in the >1eV range. The miscalibration area (A mis ) is in the higher range of what we have observed so far. The A mis metric is based on the assumption that the distribution of Z-errors (that is errors in fractions of the corresponding uncertainty) is Gaussian distributed (width=1). Figure shows the Z-distribution for the errors/uncertainties of this model, which clearly does not follow the Gaussian distribution. Note however, that according to the Var(Z) ? = 1 test, these uncertainties are accepted as being average calibrated (⟨ Var(Z)⟩ = 1.03, Table )). Since the optimum values of both NLL and Spearman's rank correlation coefficient are highly dependent on the nature of the test set and model itself (which defines the test set uncertainty and error distributions), the information that can be gained from these metrics in themselves is limited. This highlights the need for suitable reference values (NLL sim and ρ sim rank ). However, in this case the observed NLL is within one standard deviation of the simulated value and does imply any problem with the uncertainties.