{"id":"W4390535844","doi":"10.1016/j.matt.2023.12.008","title":"Catalyst design for electrochemical CO2 reduction to ethylene","year":2024,"lang":"en","type":"article","venue":"Matter","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":63,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Ethylene; Catalysis; Reduction (mathematics); Electrochemistry; Chemistry; Organic chemistry; Electrode; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001138465,0.000101183,0.00009816795,0.0000965923,0.00004022424,0.00006497384,0.00008878073,0.00007387397,0.0006171635],"category_scores_gemma":[0.000008512906,0.00009383664,0.00008109739,0.0001861997,0.00001373802,0.00006545026,0.00002248,0.00008442456,0.0009564334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009013992,"about_ca_system_score_gemma":0.00001934691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007503094,"about_ca_topic_score_gemma":0.000003192811,"domain_scores_codex":[0.9992887,0.00001394737,0.0001398677,0.0002728763,0.00008726263,0.0001973701],"domain_scores_gemma":[0.9996769,0.00002216824,0.00001209279,0.0001958161,0.00003405214,0.00005896056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00003509741,0.00001370619,0.000001202851,0.00003900122,0.00002278603,0.00000136785,0.000129674,0.00002697425,0.6526216,0.00106007,0.3369533,0.009095223],"study_design_scores_gemma":[0.00004027308,0.00004132414,0.000006926442,0.00001848682,0.00001968473,0.00005084165,0.00001643936,0.00008272683,0.6969222,0.002258851,0.3004373,0.0001049304],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1509965,0.0009535417,0.8004873,0.03137415,0.002190082,0.001442648,0.0000224721,0.001970203,0.01056301],"genre_scores_gemma":[0.9758685,0.000007242716,0.006111771,0.0007053134,0.0007281236,0.0004759454,0.00008190387,0.00005509649,0.01596614],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.824872,"threshold_uncertainty_score":0.9998214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01619758698372586,"score_gpt":0.2694086010551516,"score_spread":0.2532110140714257,"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."}}