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1 results in we demonstrate that MC-DDFMs are able to achieve near-benchmark performance on systems not used for training with a ro- bust degree of active space independence. This data-driven approach holds particular promise for the development of new functionals for multiconfigurational pair-density functional theory (MC-PDFT) in Keywords: we demonstrate that MC-DDFMs are able to achieve near-benchmark performance on systems not used for training with a ro- bust degree of active space independence. This data-driven approach holds particular promise for the development of new functionals for multiconfigurational pair-density functional theory (MC-PDFT)