{"id":"W4391432005","doi":"10.1016/j.checat.2024.100906","title":"Smart design strategies of metal-based compounds for electrochemical CO2 reduction: From microscopic structure to atomic-level active site","year":2024,"lang":"en","type":"article","venue":"Chem Catalysis","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Science Foundation of Hunan Province; National Natural Science Foundation of China","keywords":"Nanotechnology; Nanostructure; Electrosynthesis; Electrochemistry; Materials science; Renewable energy; Biochemical engineering; Computer science; Chemistry; Engineering; Electrode; Electrical engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009564808,0.0002884353,0.0004826157,0.0002251875,0.00008460977,0.0001126828,0.0002521236,0.0001731584,0.0002710484],"category_scores_gemma":[0.00002834251,0.000279796,0.0003326187,0.0007341221,0.0001000791,0.0001904089,0.00004713642,0.0001833831,0.00002021036],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002546273,"about_ca_system_score_gemma":0.0002500472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006423938,"about_ca_topic_score_gemma":0.00009316189,"domain_scores_codex":[0.9984657,0.00003112544,0.0003848482,0.0006171672,0.0002153177,0.0002858612],"domain_scores_gemma":[0.9989805,0.000120936,0.0001012886,0.0005058104,0.0001823693,0.0001091243],"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":[0.0001796946,0.00004432066,0.000002124885,0.00008830623,0.0004571165,0.000001784396,0.0004059369,0.0001708747,0.9923876,0.0005548834,0.00286898,0.002838387],"study_design_scores_gemma":[0.0002215211,0.00007261866,0.00002152881,0.00005028961,0.0004779835,0.00001197066,0.0003708274,0.0004654639,0.9868891,0.003659011,0.007500132,0.0002595468],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9245454,0.0006885441,0.07235949,0.000398348,0.0003099134,0.0004600499,0.0005856931,0.0003442397,0.0003083383],"genre_scores_gemma":[0.9823287,0.00001001448,0.01449393,0.00003249404,0.0002311284,0.0001492674,0.002256508,0.00005341141,0.0004445177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05786556,"threshold_uncertainty_score":0.9999654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02106051873218351,"score_gpt":0.270826039858497,"score_spread":0.2497655211263135,"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."}}