Conversely, if a human-understood descriptor is accessible to a model's understanding in the embedding space, it may provide the model with a more knowledgeable embedding initialization. In terms of hybridization, consider the case where hydrogens are implicit in a graph, described as a node level feature from 0 to 4 that corresponds to the number of hydrogen atoms bonded to that node. If a carbon is connected to three carbons and has one implicit hydrogen, it is readily apparent that that node will be equivalently sp 3 hybridized and will have comparable vibrations for any C-C bonds. However, the relative equivalence of these systems may not be evident to the model, and it may take several epochs to learn the similarities in these two graphs, which could be perhaps better spent discerning more subtle chemical interactions. This time spent learning could be eliminated by providing that initial description of hybridization, which has the potential to improve model scores by starting from a more sophisticated initial description. Explicit labels of hybridization may also prove helpful in discerning more complicated cases that break conventional bonding rules, like in the expanded octets of sulfur and phosphorus that are sp 3 d and sp 3 d 2 hybridized and bonding motifs may be less intuitive from graph structure.