where n is the number of features, f 1≤a≤n (⃗ r), used to define the local xc energy density, e xc . For B3LYP there are five ingredients, of which only four are used non-trivially and all are employed analytically -it is thus easy to understand how B3LYP (mis-)behaves. In contrast, understanding how DM21 varies with its n = 12 ingredients (i.e. dimensions) is a virtually impossible task. We can, however, get some insights into the kinds of features that DM21 has learned, and those it needs to deal with in systems where it wasn't trained on. Combinations of features that do not appear in the training data are the most likely source of errors in failure cases. For this task, we represent the features of a system using two-dimensional projection heat maps,