The fact that these reactions should also be correct and generally "ordinary" enhances the ability to evaluate the performance of the model. Additionally, to test the validity of the retrosynthetic predictions, all predicted retrosyntheses were run through the forward prediction model. Results were collected in a data set along with metrics returned from IBM RXN for each prediction, such as confidence and optimization scores. Characteristics of the predicted retrosynthetic pathways were assessed using the difference of molecular complexity and synthetic accessibility from reactants to products. Molecular complexity was evaluated using an implementation of Böttcher's 2016 additive definition of molecular complexity (Cm). Our script for computing molecular complexity is available as a GitHub repository 20 as well as through the Wolfram Function Repository as a resource function. Ertl and Schuffenhauer's measure of synthetic accessibility (SA) is readily available in Mathematica and in the Python RDKit. The differences, ∆Cm and ∆SA, were computed as the cumulative score of the product(s) minus the cumulative score of the reactants for all literature reactions, as well as all retrosynthetic and forward prediction reactions.