We now present a comparison of the D-MPNN prediction performance, focusing on the different multifidelity learning approaches, to conclude if one is more suitable than the others. We then compare these models with other existing models from the literature that can be used for toluene/water partition coefficient prediction to evaluate the multi-fidelity learning approaches overall.