We mentioned previously that the neighbor test yields near perfect results when hydrogens are removed without the subsequent optimization step for any oxidation reaction. The difference in performance between the optimized and non-optimized results is chemically meaningful, and can be best illustrated in the case of oxidation of an alkane. In such a reaction, it is possible to have either the cis or the trans product, which are stereoisomers of each other. A closer look at the oxidation vectors to both isomers we find a difference in the cosine similarity of the reaction vector going to trans vs going to cis. For the cis isomers, the high-dimensional cosine similarity of the embedding is consistently larger at an average cosine similarity of 0.95, whereas for the trans isomers, an average cosine similarity of 0.91 is obtained with respect to the mean reaction vector embedding. The difference between the cis and trans cosine similarities with respect to the mean reaction vector is significant according to an independent samples t-test which gave a p-value of 1 × 10 -4 . The neighbor test using the average reaction vector yields slightly better results on cis (67.1%) than on trans (54.9%), which implies that it is biased towards cis geometry, as QM9 has many alkanes inside rings. This explains part of the discrepancy in the neighbor test going from non-optimized to optimized, as product alkenes determine which shape they will hold implies that a single average reaction vector approximation for all possible optimized states becomes a biased assumption. Additionally, we performed MMFF94 geometry optimization on our new products for efficiency, whereas the QM9 dataset, and correspondingly the SchNet model, is optimized at the B3LYP/6-31G(d,p) level of theory. Both of these discrepancies may be slightly affecting the results, nonetheless, even with these approximations it is clear that geometry optimization plays only a minor role to that of chemical composition in mapping out the chemical embedding space.