1. The scarcity of accurate benchmark data for transition metal chemistry is a well-known issue despite recent improvements . For example, the TMC151 database has about ten/thirty times fewer reactions than the GMTKN55/MGCDB84 databases for main-group chemistry. Moreover, within the TMC151 subsets, only TMD60 uses a higher level of theory than CCSD(T), which is a single-reference method. To address this data scarcity, one can either utilize existing or design new data-efficient strategies for machine-learning DFAs.