Figure (d) confirms that the standard deviation of predictions over model ensembles is a useful uncertainty metric in this modeling application, but with some limitations. The individual residuals for any given test prediction (blue circles) are only very weakly correlated with σ({MAE} K ). However, computing the average and standard deviation of residuals within a given bin of σ({MAE} K ) (red markers and error bars, respectively) collapses the data onto the y = x parity line (cyan). Therefore, on average a low σ({MAE} K ) is correlated with a low residual, but there is a non-negligible probability of individual predictions with very large residuals despite low uncertainty.