Finally, Crystal-Olfaction was challenged to distinguish between not just structurally dissimilar molecules, but between enantiomers, distinguished by a one-hot coded chiral tag. It is well understood that whilst their physical properties are identical, enantiomers can be perceived as two distinct scents. A classic example is that of carvone, where (R)-carvone is often described as spearmint and (S)-carvone as caraway. Thus, 11 enantiomer pairs, 5 of which have identical olfactive profiles and 6 which have distinct olfactive profiles were chosen. Crystal-Olfaction and the baseline models were trained on all training data folds and tested on these 22 compounds (Figure & Figure ). It was noted that all found this new test set difficult, although Crystal-Olfaction performed significantly better than baselines (Table ). Given baseline models' difficulty in distinguishing odor classes on structurally dissimilar molecules, it is unsurprising that enantiomer distinctions were similarly challenging (Figure ). Crystal-Olfaction was more accurate at determining the correct scent labels, however, its ability to distinguish between enantiomeric olfactive profiles was more limited. Of the 11 pairs, 5 were correctly identified as having identical or different fragrance notes (Figure ). Commonly, Crystal-Olfaction would predict identical odor classes for enantiomers with substantially different scents. However, some successes were noted: the differentiation between menthone enantiomers 23 and 24 and of enantiomers 19 and 20. Whilst the none of the top 5 predicted labels for 19 were correct, it was observed that a "fermented fatty" odor could be construed as cheesy, a label that Crystal-Olfaction deemed highly likely for 19. The challenge of this test set is highlighted in the low density (5%) of chiral molecules in the training dataset, of which only 21% of those chiral molecules were enantiomeric pairs (Figure ). Inclusion of additional chiral molecules into the training set may yield more discernment between enantiomer pairs.