There are two models of primary interest: a single-label model trained on the highest yielding context for a reaction and a multi-label model trained on all available data. Both models are feed-forward neural networks that use reaction fingerprints as inputs and give chemical contexts as outputs. A chemical context here is a combination of chemicals added to the reactants (see exact definition below).