In real life applications, in particular in Drug Discovery, only molecules are of interest that are readily synthesizable. Many different measures of synthesizeablity have been proposed in the literature, see e.g. for a recent overview. SAScorer, for instance, is pretrained on PubChem data and focusses on structural features. Penalties are given for large number of atoms, spiro centers, and bridges . A lower score is associated with an easier access through synthesis. An alternative is to use SCScore, which is trained on reaction networks with the thought that synthetic complexity increases with the expected number of reaction steps. A higher score then indicates more steps required for synthesis. Distributions of synthesizability scores using both tools on the 10-sample molecule recombinant set are summarized in Figure . As expected, we observed that the score distribution of crossover products is less favorable than the starting molecules. Nevertheless, the distributions show a large overlap and crossover products even with very good scores are not particularly rare.