{"record":{"author":{"account_ref":null,"orcid":null},"builds_on":[],"content_schema":"pubphys.content.revision/1","content_sha256":"abf079b4a9cc1444244774189a1d0c3c35dcffce24672c5d7eb1ccd0893449e1","created":"2026-10-03T07:17:58Z","files":[],"origin":{"assisted_by":[],"kind":"seed"},"parents":["5475cf5dc5b1a72283d26dc95dc6e00d7ea4e00096a7c6492e409a1816eeb011"],"salt":"8f4d240fa94980c74fbd702aaf6d80aadb6a2d29b10aceb3579ddbf810010c99","schema":"pubphys.record/2","site":"pubphys.com","target":null,"type":"revision"},"content":{"answer_type":"value","assisted_by":[],"external_id":"chem.dft-functionals.ml-transferability","kind":"well-posed","literature_status":"open","n":"1","parents":[],"plain":"Functionals fitted by machine learning to accurate data now beat hand-made ones on molecules similar to their training set. It is unknown whether they stay accurate for metals, transition-metal compounds and solids they never saw.","posed_since":"","precise":"For a machine-learned exchange-correlation functional trained only on main-group molecular data, determine its errors on out-of-distribution sets: 3d transition-metal reaction energies and spin gaps, lattice constants and cohesive energies of metals, and band gaps of solids, relative to the best conventional hybrid. An answer is a quantitative transfer test, or a training principle (exact constraints, data types) shown to guarantee transfer.","problem_ref":null,"references":"","settled_by":"Blind evaluation of trained functionals on held-out transition-metal and solid-state benchmarks with reference data from coupled cluster, quantum Monte Carlo and experiment.","status_note":"Learned functionals released from 2021 to 2025 improved main-group thermochemistry; transfer to transition metals and solids is not established.","title":"Transferability of machine-learned functionals beyond their training chemistry","topic_ref":"3c4f63964447b45aecf4c4997f101268b15cc64d8f6c4f7f7f8c32e958440823"},"attested":{"attestation":{"batch":null,"client_id":null,"id_token_sha256":null,"kind":"platform"},"record_hash":"a7a199943e51ec93d1d64a06edb74ec7352b88e2f9703fa5a2f92552ff32f5f0","schema":"pubphys.attested/1"},"envelope":{"attested_hash":"4f414e89e487e1768e97714145dbc56b7343474905dd18b2789becf576637a91","platform_signature":{"key_id":"c6afc19b31429869751f06879c75cd64ea92654423d15b44be775bf1310a60da","sig":"SLHYbVQrhXFK-d2PMupA0C69qUbrLYSYH9NheIDSfcXagmv5JcnmIABHtvy4via8T4Aud_CJauOIN5iBe-bTBg"},"schema":"pubphys.envelope/1"},"record_hash":"a7a199943e51ec93d1d64a06edb74ec7352b88e2f9703fa5a2f92552ff32f5f0","leaf_index":860}