Taken together, an uncertain diverse model may lead to more model calls as it promotes exploration in the tree search. The multi-step efficiency of a single-step model thus depends on the overall feasibility and quality of the predicted top-10 reactions. Moreover, the ability to properly rank predictions becomes important, something which is difficult to assess in a single-step setting. While all predictions produced by the single-step model affect the multi-step performance, top-10 only considers the best prediction.