When comparing the expert decision trees to the decision tree algorithm, both similarities and dissimilarities are observed. Again, the first node regards the C-2 substituent, more precisely whether it is a -1 configuration (assigned using the donor vector). In most cases, this corresponds to an equatorial orientation of the C-2 substituent. The next question when following the tree to the left branch is whether the C-2 substituent is an O-benzyl, which can be seen as an indirect question of whether NGP is possible, or in this case not possible (O-benzyl is the most abundant C-2 substituent after O-acetyl). If the C-2 substituent is an O-benzyl group, the algorithm queries whether the solvent is acetonitrile which would give β-selectivity. This branch is similar to the expert decision trees, though it seems that specifying that the C-2 substituent is an O-benzyl seems to improve the assumption that if the glycosylation is not run in acetonitrile, it is α-selective. If the C-2 is not an O-benzyl, the next question is whether the C-2 substituent is an azido-group, if so, the glycosylation is α-selective. This effect, sometimes referred to as the azido method, was first described by Hans Paulsen in 1975 and has subsequently been widely used, mostly in galactosylations. The effect is often attributed to the N3-group being non-participating, and the degree of the effect is controlled by other factors. However, it is interesting that it is introduced early in the algorithm decision tree and not at all in the expert decision trees, which could indicate the 2-azido group itself plays a bigger role and is α-directing rather than just not being β-directing. This is substantiated by the fact that the solvent is not queried after, as it is for the C-2 O-benzylated donors, and a recent study showing that an azido group on the C-2 can act as a hydrogen-bond acceptor in combination with specific activators. If the C-2 is not an O-benzyl nor an azido, the algorithm asks whether the donor is or is not a derivative of the anti-malaria drug dihydroartemisin (illustrated in Figure ). This is surprising as it is a highly specific decision node and only the fourth node, which is likely due a significant interest in dihydroartemisin's anti-malaria properties within the timeframe of the dataset. It is also seen that dihydroartemisinin is not a classic carbohydrate but resembles some of the characteristics, more specifically the lactol part, making it fit into our rather broad definition of a glycosylation reaction when creating the dataset. This explains why the behavior of these types of donors are different i.e. need their own decision node. If the donor is not a dihydroartemisinin derivate, the glycosylation is predicted to be β-selective, hence carbohydrates with an NGP-substituent on C-2 would fall into this group, but also non-NGP-substituents except from O-benzyl and azido groups. Assuming βselectivity for these glycosylations seems reasonable as it is correct approximately 9 out of 10 times.