Many settings used in a DFT calculation can affect the absolute energy, and as more datasets appear they will likely have small (or large) differences which would give one pause when combining the data naively. Examples include seemingly minor modifications of a functional (e.g. ωB97X, ωB97X-D, ωB97X-D3), similar but incompatible basis sets (e.g. def2-TZVP, def2-TZVPD), the use of integral approximations such as density fitting or pseudospectral approximations, use or lack of a pseudo or effective core potential and even various integral, self-consistent field convergence, and linear dependence thresholds. Nonetheless, each new dataset entering the literature brings some new value. It is desirable to use methods which are able to extract valuable information from all datasets appearing in the public domain without the need to relabel them, in order to build a more general, transferable model.