For every score and its optimal threshold, we computed the prediction accuracy of AiZynthFinder's outcomes. We also measured the quality of scores by calculating the area under the ROC curve (AUC) which describes the probability that a score ranks a randomly chosen synthesizable molecule better than a randomly chosen non-synthesizable molecule. Results are depicted in Table . For both AUC and accuracy, SAscore and RAscore achieves high results (AUC and accuracy were both over 0.81). On the contrary, for both SCScore and SYBA, the results are worse by about 20 percentage points. RAscore's good result is not surprising, because it was trained on the outcomes of the AiZynthFinder algorithm. This, combined with the low sensitivity of AiZynthFinder, allows us to claim that RAscore is a