An analysis of the changes of feature importance when training with the LEF4000 and tranche 1 as opposed to just the LEF4000 suggested two main reasons for the performance difference. The first reason was the appearance of new features in tranche 1 and tranche 2 that had not been present in the LEF4000. As explained above, the expansion of the LEF4000 was intended to explore new chemical space, which added new fluorine environments encoded as fingerprint bits into the set. Figure visualizes a CF substructure feature present in tranche 1 and tranche 2 but not present in the LEF4000. The closest analogs to the fluoropyrrolidine substructure carrying the hydroxymethyl shown in Z2051927854 in the LEF4000 were four fluoropyrrolidines, which had acids or amides in place of the primary alcohol as well as a different stereochemical configuration. These significant structural differences in the closest analogs of the LEF4000 resulted in poor predictions of the 19 F NMR chemical shift. The highlighted fingerprint feature was the one with the highest gain feature importance after the addition of tranche 1 that described this substructure. Other fingerprint features with non-zero feature importance after training with the LEF4000 and tranche 1 also encoded parts of the fluoropyrrolidine. A combination of these bits was likely used by the GBT model to predict the 19 F NMR chemical shift. Training with only the LEF4000 resulted in predictions with a MAE of around 6 ppm for these fluoropyrrolidines in tranche 2. Training with the LEF4000 and tranche 1 managed to improve this to a MAE of around 1 ppm by providing more examples of these bits to the GBT.