It should be noted here that the fact that a model, trained on a combination of the original BH9 subset and the acquired reactions, generalizes much better across the designed chemical space, suggests that this resulting, expanded dataset is significantly more representative of the selected chemical space than a (subset of) the original benchmarking dataset. As already indicated, after 7 rounds, the exploration stage of the BO campaign was stopped, as the σ of the newly acquired data points had barely improved with respect to the previous rounds, and the MAE of the predictions appeared to approach convergence. Some examples of the best reactions emerging from the exploration stage are shown in Figure , with the selected substituents highlighted. Substituents that extend the delocalization, such as phenyl or ester groups, as well as voluminous groups introducing steric hindrance, turn out to be key for increasing the σ of the activation energy values.