The correlation between the populations of the trans conformer for the predicted ensemble and the experimental observable for compounds I1 and I4 is shown in Figures and for the GB-Neck2 and GNNIS models, respectively. For both compounds, the expected linear relationship between the predicted trans-conformer population and J tot is observed for the ensembles minimized with OpenFF 2.0.0 and the GNNIS model. The results indicate that the proposed workflow can rapidly provide such solution ensembles and represents a significant improvement over the GB-Neck2 model. One interesting aspect of these results is that the relative populations of the opened and closed conformations of compound I1 do not align with the perception that polar solvents should favor more open conformations, as can be seen in the GB-Neck2 results. As the GB-Neck2 model relies solely on a continuum description using a fixed dielectric constant, the predicted populations are dependent on this property. Water, DMSO, and methanol, which feature the highest dielectric permittivities, are predicted to have the greatest fraction of the trans conformer (conversely, benzene, with the lowest dielectric permittivity, is predicted to have the smallest fraction of the trans conformer). While this is true for DMSO, water features one of the lowest populations of the trans conformer for both compounds I1 and I4. Further investigation revealed that the reason for this is the ability of water to form an H-bonding network with the compound (see SI Figure ), thus stabilizing the closed conformation. The fact that the GNNIS model can capture the effects of these complex interactions is especially promising. The two main outliers are acetonitrile and THF for compound I1 (left panel of Figure ) for which the prediction diverges from the linear trend. However, the explicit-solvent simulations of compound I1 in these solvents (see Section "Prospective Simulations") indicate that this deviation may not be due to the GNNIS model itself but rather to the explicit-solvent model that was used to generate the training data. The predicted fraction of the trans conformer based on the explicit solvent simulation (2.9% and 6.0% for acetonitrile and THF, respectively) is very similar to that predicted by the GNNIS minimization approach (2.3% and 4.9% for acetonitrile and THF, respectively).