In earlier local correlation methods, PAOs are assigned to each LMO based on sparsity. Since there is a constant number of significant PAOs per LMO, these methods approach linear-scaling. PAO-based local correlation methods represent the first generation of linear-scaling post-Hartree-Fock methods, and are forerunners to pair natural orbital (PNO) based approaches. In DLPNO-based algorithms, assigning PAOs to each LMO is done as a precursor before PNOs are computed, to ensure the linear-scaling of PNO generation. In our work, following Pinski, Riplinger, Valeev, and Neese, PAOs are assigned to each LMO based on spatial overlap, computed through a measure called the "differential overlap integral" (DOI)