Clearly all models have problems with local miscalibration (either under-or overestimated uncertainties). However, since the miscalibration area, A mis , evaluates average calibration (assuming Gaussian errors) only the general miscalibration of the two models with N train = 100 and N train = 500 is caught (Table ). The remaining seven models show close to perfect miscalibration areas. From the error-based calibration plots (Figure ) we see that the zero miscalibration area stems from a cancellation of the local miscalibrations: the under-and overestimated uncertainties cancel in the calculation of A mis .