Moreover, we checked in-depth if synthetic accessibility scores can correctly discriminate internal nodes from not solved ones and solved nodes from not solved ones. We collected all internal, solved, and not solved nodes. To find a threshold properly discriminating AUC nodes, we analyzed ROC curves of synthetic accessibility scores, cf. Figure and Suppl. Figure . AUCs are depicted in Figure . Practically, all scores except SYBA correctly discriminate internal nodes from not solved and solved from not solved. Note that for each of the rest of the scores, only the mean and minimum aggregating functions are efficient. It is because minimum detects the presence of non-synthesizable outliers while maximum reports the best synthesizable molecules. Analogously as earlier, SAscore achieved the best results and RAscore was slightly worse. The rest of the scores were considerably worse. Finally, we analyzed if directly replacing a fraction of the reward with an appropriately scaled synthetic accessibility score may boost the retrosynthesis planning as in Equation . If so then nodes during leaves selection would be better prioritized by UCB and thus computation time decreased. However, it turned out that this replacement did not improve significantly any parameter of search tree complexity (cf. Supplementary Tables ). It may be caused by undermined reward fraction in UCB formula or high fitting of search algorithm design to its internal scorings.