{"id":"W4225474811","doi":"10.1021/acs.jctc.2c00036","title":"Small-Basis Set Density-Functional Theory Methods Corrected with Atom-Centered Potentials","year":2022,"lang":"en","type":"article","venue":"Journal of Chemical Theory and Computation","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Okanagan University College; University of British Columbia, Okanagan Campus; University of British Columbia","funders":"British Columbia Knowledge Development Fund; Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España; University of British Columbia; Ministerio de Ciencia e Innovación; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Basis set; Thermochemistry; Density functional theory; Coupled cluster; Basis (linear algebra); Atom (system on chip); Non-covalent interactions; Computational chemistry; Set (abstract data type); Cluster (spacecraft); Chemistry; Atomic physics; Molecule; Statistical physics; Physics; Computer science; Quantum mechanics; Physical chemistry; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001645106,0.001760744,0.00257397,0.001621632,0.001534274,0.001124409,0.004672985,0.00221911,0.009327503],"category_scores_gemma":[0.003284497,0.000531324,0.001729436,0.003056857,0.0006573288,0.001332351,0.001506556,0.00382087,0.004170137],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0010902,"about_ca_system_score_gemma":0.00278651,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004558247,"about_ca_topic_score_gemma":0.005900333,"domain_scores_codex":[0.9985484,0.0005019802,0.00006310962,0.00007760491,0.0006900004,0.0001187464],"domain_scores_gemma":[0.9983536,0.0005926669,0.00007340484,0.0003532547,0.0005622504,0.00006485749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003457564,0.0003753623,0.00122278,0.002734208,0.0005062916,0.0006392589,0.0002084447,0.5501966,0.009267833,0.2014517,0.03921078,0.193841],"study_design_scores_gemma":[0.0001401825,0.0001007863,0.0004468147,0.0001342391,0.00005152927,0.00009888859,0.00003749896,0.9544534,0.004152839,0.01998223,0.02032556,0.00007604559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03095112,0.006317628,0.9257054,0.0006979348,0.0009952704,0.000855413,0.002934458,0.003155551,0.02838716],"genre_scores_gemma":[0.2533727,0.006889017,0.7127703,0.0007194448,0.0003328369,0.004219952,0.006297874,0.002082523,0.01331531],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.009327503,"threshold_uncertainty_score":0.03120363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02500699143298366,"score_gpt":0.296773891957429,"score_spread":0.2717669005244453,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}