With these settings, active learning completed after adding 780 structures, i.e. 31% of the candidates and 9% of the total landscape. This is significantly higher than seen for oxalic acid or TTBI, illustrating the impact of a poor correlation between the baseline (DFTB-D3) and target (DFT-D3) methods, increasing the complexity of the function that the model is attempting to fit. The corrected landscape evaluated with the final potential is presented in figure . Out of the 8808 structures, 19 had uncertainties above 6 kJ mol -1 and were evaluated directly with the target method. Examining these structures, most were only slightly above the threshold and the predicted energies were close to the computed energies, suggesting that the cutoff at 6 kJ mol -1 may have been tighter than needed.