Since the chosen cutoffs are somewhat arbitrary, we also investigate the subset of 426 molecules with only one unique experimentally observed reaction site and where RegioSQM20* only predicts one unique (green) reactive site. Here, RegioSQM20* is compared to the top-1 WLN prediction and the success rates for WLN and RegioSQM20* are 96.0% and 92.0%, respectively. A similar comparison to RegioSQM18 by Struble et al. for a different set of molecules (not used to train the WLN method) yielded 87.9% and 86.7%, respectively. The relatively large difference in success rates observed for WLN for these two sets of molecules could indicate that many of the molecules used in the current data set are included in the WLN-training set. Overall, the success rates of RegioSQM20 and the WLN-based method are thus comparable, while the latter is orders of magnitude faster.