{"id":"W4407041620","doi":"10.1021/acs.langmuir.4c04638","title":"Automated Machine Learning of Interfacial Interaction Descriptors and Energies in Metal-Catalyzed N<sub>2</sub> and CO<sub>2</sub> Reduction Reactions","year":2025,"lang":"en","type":"article","venue":"Langmuir","topic":"Machine Learning in Materials Science","field":"Materials Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Education and Child Care","funders":"National Key Research and Development Program of China Stem Cell and Translational Research; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Catalysis; Chemistry; Electronegativity; Redox; Dimensionality reduction; Transition metal; Reactivity (psychology); Metal; Computer science; Inorganic chemistry; Machine learning; Organic chemistry","routes":{"ca_aff":true,"ca_fund":false,"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":[0.000525995,0.0006137611,0.0005359146,0.0004956169,0.0001913795,0.0004571498,0.0005480486,0.0004639198,0.0008224667],"category_scores_gemma":[0.001477723,0.0002952635,0.0005251247,0.0003862698,0.0002419097,0.0005208118,0.0004049732,0.0005360842,0.0001611395],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005793276,"about_ca_system_score_gemma":0.0004838807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002407165,"about_ca_topic_score_gemma":0.002560348,"domain_scores_codex":[0.9998692,0.00005631273,0.000007347503,0.00003398919,0.00001855037,0.00001445756],"domain_scores_gemma":[0.9995204,0.0003563302,0.00004028737,0.00003044587,0.00004146807,0.00001107368],"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":[0.0001902872,0.0001952282,0.004254533,0.00007738679,0.00005869337,0.00006843881,0.00006407843,0.8665069,0.01799082,0.001077881,0.0007269654,0.1087888],"study_design_scores_gemma":[0.000002626037,0.000007115677,0.0002448794,4.073993e-7,0.000001329614,0.000002031043,0.000002826752,0.9977542,0.001694515,0.0002509801,0.00003758479,0.000001636326],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5571215,0.0001103909,0.4381545,0.0001460773,0.00001237808,0.0000626705,0.000295888,0.003108273,0.0009884012],"genre_scores_gemma":[0.9021109,0.00004162121,0.09667625,0.00002789273,0.000005606022,0.0001346944,0.000403916,0.00007696289,0.000522188],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002407165,"threshold_uncertainty_score":0.004786372,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01101455148060663,"score_gpt":0.267018330465013,"score_spread":0.2560037789844063,"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."}}