For the analysis, we extracted all predicted routes that are solved, but if a target is not solved, we extract at most 25 routes. We can observe that MCTS and Retro* produce roughly equal amounts of routes, the median number of produced routes are between 149 and 273. On the other hand, DFPN produces very few routes, the median is only 6 routes. Considering that it does find solutions for close to 85% of the targets, it seems the problem with DFPN lies in its ability to find alternative solutions. This is also reflected in the lower top-5 and top-10 accuracies discussed above. The CompRet implementation of a DFPN algorithm was able to find a considerably large amount of routes for a rather small set of compounds [27], so it is possible that our implementation is inferior to CompRet in this regard. Finally, it should be noted that the distribution of the number of produced routes is heavily skewed for Retro* and DFPN, see Figure , whereas it is comparatively uniform for MCTS.