{"id":"W4309391467","doi":"10.20944/preprints202211.0334.v1","title":"Optimal Icosahedral Copper-based Bimetallic Clusters for the Selective Electrocatalytic CO<sub>2</sub> Conversion to One Carbon Products","year":2022,"lang":"en","type":"preprint","venue":"Preprints.org","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of British Columbia","funders":"Engineering and Physical Sciences Research Council; Queen Mary University of London","keywords":"Bimetallic strip; Catalysis; Formic acid; Inorganic chemistry; Selectivity; Carbon monoxide; Chemistry; Overpotential; Formaldehyde; Methane; Copper; Methanol; Electrochemical reduction of carbon dioxide; Carbon fibers; Materials science; Electrochemistry; Physical chemistry; 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":[0.0001031589,0.0003239117,0.0003356338,0.000222941,0.0004752675,0.0006081008,0.0006119518,0.0005397924,0.002650121],"category_scores_gemma":[0.0003938043,0.0002811192,0.0002267288,0.0002267079,0.0002809622,0.0004252068,0.0003079206,0.0003047324,0.0003059971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009568522,"about_ca_system_score_gemma":0.000520649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004636302,"about_ca_topic_score_gemma":0.008928945,"domain_scores_codex":[0.9999442,0.000006967309,0.00000234795,0.00001191635,0.00001311769,0.00002137569],"domain_scores_gemma":[0.9999429,0.00002024214,0.000008789603,0.000007517601,0.00001233486,0.000008282179],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008813156,0.0004358339,0.006490554,0.001397912,0.0001826726,0.0006199138,0.0002986691,0.7376253,0.186683,0.02702797,0.006818099,0.03153881],"study_design_scores_gemma":[0.000265633,0.0006037072,0.004639554,0.00006291571,0.000132506,0.0001612931,0.0004669777,0.8864217,0.09419873,0.006494167,0.006508443,0.00004448829],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9838705,0.0005597209,0.006697228,0.000182834,0.00003700748,0.00003696289,0.0002489461,0.0001479035,0.008218898],"genre_scores_gemma":[0.9927689,0.0001994633,0.005998798,0.00002570236,0.000003435079,0.00005223278,0.0002021898,0.00003796147,0.0007113155],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004636302,"threshold_uncertainty_score":0.009218574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05332686073615675,"score_gpt":0.3022409737485607,"score_spread":0.248914113012404,"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."}}