As discussed in the introduction, limiting the NN training to just the LMF of a humandesigned flexible but well-defined LH, rather than deep-learning the entire functional as for example in the case of DM21, opens the possibility to examine the shape of the resulting LMF. This can be done in comparison with other known LMF models. Given the training for valence energy differences, the valence region and the intermediate region towards the asymptotics are more interesting to analyze. Regarding the latter aspect, the n-LMF reaches the plateau later than the t-LMF albeit with a similar slope. Notably, the n-LMF exhibits additional narrower peaks on each side outside the bonding region before this rise, much more pronouncedly on the side of the more electronegative oxygen atom. This seems to hold true also for other heteronuclear diatomics like CO (see Figure in Supporting Information). We note in passing that the so-called density-overlap regions indicator (DORI), which also has been used