To further qualify the differences in the potential, we generated a test set of 1000 unminimized structures, randomly sampled from FIT+DMA MC simulations of the α and β polymorphs. The MC simulations sampled an energy up to 20 kJ mol -1 above the initial energy and were sampled evenly such that 500 structures were from the α polymorph trajectory and 500 were from the β polymorph trajectory. The correlations of energies for these structures calculated by PBE-D3 against those calculated by FIT+DMA, the cNNP trained on CSP minima, and the cNNP with on-the-fly training are shown in Figure . Considering first FIT+DMA, there is a notable and pronounced systematic underestimation of the energies for the α polymorph structures and yet simultaneously a systematic overestimation for the β polymorph structures. These inconsistent errors reflect the difficulty in accurately capturing the oxalic acid energy surface with the simple functional form and thus emphasizes the limitations of the the FIT potential for this system. By contrast, the cNNP trained on CSP minima does not exhibit similar systematic errors, and for most structures achieves low errors. Indeed, for the structures sampled from the β polymorph trajectory the model achieves a significantly lower MAE than FIT+DMA. However, the limitation of this model, and the cause of the unstable downhill MC trajectories, is a small number of structures that the model returns excessively large errors for, often more than 100 kJ mol -1 . The effect of these outliers can be seen in the RMSEs, which are multiple times larger than the MAEs. Pleasingly, the uncertainties on the outlier predictions are similarly large. For example, removing structures with uncertainties above 10 kJ mol -1 for the α trajectory structures, which corresponds to 72 structures (from 500 total), we find the underlying MAE and RMSE to be 1.56 and 2.03 kJ mol -1 , respectively. Therefore, while the extrapolation of the model is better than expected for the majority of structures, highlighting the broad relevance of potentials trained on CSP minima, the prevalence of outliers suggests an incomplete description of the energy surface.