As seen, both xTB-CC-TL and xTB-B3LYP-CC-ML have similar performance on the test set, and perform slightly worse than xTB-CC-ML. It is difficult to tell a priori which of these models would generalize better, although both would certainly generalize better than the simple xTB-CC-ML model, which does not consider external data at all. For ease of comparison in the future, we have applied all 3 models to the existing datasets. While it would be ideal to have CC2 energies for these datasets, unfortunately this would be prohibitively expensive to generate for the large number of molecules required to obtain a meaningful error value. We have therefore left this analysis for a future work, but have uploaded the ML CC2-calibrated values of all datasets to Github. Overall, xTB-CC-ML serves as a interesting proof of concept that can be expanded further in the future, perhaps with additional CC2 calculations on more diverse molecules.