To summarize, MSE in V res and C Pres , derivatives of Gibbs energy in pressure and temperature dimensions, primarily guide the optimization. We have made this choice as molar volume/density and heat capacity are the only observables available experimentally (regenerated via IAPWS95 EOS) for water in the liquid region. We find the contribution to the magnitudes of MSE in V res and C Pres are an order of magnitude higher than the MSE of other properties which means these two properties are the main optimization drivers. The magnitudes of MSE in other properties, although lower compared to the latter two, are constrained so that the optimization does not lose accuracy in these properties either for the entire range of temperature and pressure. We thus use information from all the derivatives. As described before, we are trying to match not only the G r esT, P surface but also its gradients and curvatures in both T and P directions. Our choice of weights (or equivalently, units) on our constraints helps the optimization to emphasize reduction of the errors in molar volume, in order to reduce the errors in properties based on pressure derivatives of Gibbs energy, while still constraining the errors in properties based on the temperature derivatives. Further discussion of the magnitude of these weights is found in the SI in section 1.2.