Figure An illustration of the data pipeline. The raw data consists of reaction SMILES, categorical reaction conditions, and temperature. A distribution of temperatures, top 10 solvents, and top 10 activators are shown. The raw data is featurized using a donor vector (to capture the stereochemistry of the donor), graph neural networks (GNN), or one-hot-encoding (OHE). From the featurized data, the anomeric configuration is predicted. Instead of assigning a common stereochemical descriptor to the anomeric configuration, a descriptor based on the configuration in a Mills projection is used.