The results are shown in Figure . Both plots show extraordinary agreement between values obtained by conventional calculation and shortcut calculation on the trained range. It is not surprising to see that the model trained on the LL data fits the training data for a wider range of operating conditions. Note, that extrapolation capabilities seem to be higher for the LL data than the SU data (compare red and pink curves in Figure ). This effect might be explained by the fact that high values are underrepresented in the training set with uniform sampling and thus cause larger errors when extrapolating.