{"id":"W4413353889","doi":"10.1002/cssc.202501180","title":"Electrochemical Transformation of Copper Sulfide Electrodes for Selective CO<sub>2</sub>‐to‐Formate Conversion","year":2025,"lang":"en","type":"article","venue":"ChemSusChem","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Université du Québec à Montréal","funders":"Agencia Estatal de Investigación; European Regional Development Fund; Horizon 2020 Framework Programme; Directorate-General XII, Science, Research, and Development; Eusko Jaurlaritza; Grantová Agentura České Republiky; European Commission; Universitat Jaume I; Diamond Light Source","keywords":"Formate; Faraday efficiency; Catalysis; Electrochemistry; Materials science; Selectivity; Copper; Inorganic chemistry; Leaching (pedology); Chemical engineering; Electrode; Chemistry; Nanotechnology; Organic chemistry; Metallurgy","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":[0.0001777892,0.0004655933,0.0002539067,0.0002494988,0.0002378139,0.0004205847,0.0003832856,0.000328288,0.0009123425],"category_scores_gemma":[0.0004110785,0.0002688007,0.0001354521,0.000279196,0.0003036622,0.0002748768,0.0002385804,0.0003694982,0.0002689099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004467996,"about_ca_system_score_gemma":0.0003030864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000872553,"about_ca_topic_score_gemma":0.00277943,"domain_scores_codex":[0.9998134,0.00002718109,0.00001471805,0.00003397621,0.00007880374,0.00003207876],"domain_scores_gemma":[0.9999088,0.00002267642,0.00001607815,0.00001159698,0.0000319683,0.000008836369],"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":[0.00004217893,0.00001466754,0.0001219527,0.00007281696,0.000009833964,0.0000743493,0.00002369302,0.0002114329,0.9925601,0.0003216861,0.0002774358,0.006269841],"study_design_scores_gemma":[0.000002288675,0.00002339769,0.0001921182,0.000001115526,0.000002509869,0.00003172677,0.000008800976,0.0008940893,0.9977405,0.0000259439,0.001075514,0.000001969025],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9548174,0.002728427,0.02967972,0.000502166,0.000282777,0.0001150254,0.0002809888,0.0005492634,0.01104426],"genre_scores_gemma":[0.9863024,0.0009362666,0.00933728,0.00005599334,0.00001968008,0.00002730209,0.0001168818,0.00002681118,0.003177422],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0009123425,"threshold_uncertainty_score":0.003241777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006239391545781303,"score_gpt":0.245767021529085,"score_spread":0.2395276299833037,"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."}}