{"id":"W4412068674","doi":"10.1007/978-3-031-98056-5","title":"Modulation Strategies of Cu-based Electrocatalysts for Enhancing Electrocatalytic CO2 Conversion","year":2025,"lang":"en","type":"book","venue":"Synthesis lectures on green energy and technology","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Modulation (music); Materials science; Electrocatalyst; Nanotechnology; Chemical engineering; Chemistry; Electrode; Electrochemistry; Engineering; Physics; Acoustics; Physical 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":[0.00007446329,0.0004305277,0.0002467739,0.0001764707,0.0001688207,0.0004635642,0.0003931042,0.0003376466,0.001162744],"category_scores_gemma":[0.0001024968,0.000224145,0.0001750672,0.0002562707,0.0001571144,0.0004042664,0.0002077064,0.000471577,0.0003887645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004036548,"about_ca_system_score_gemma":0.000103156,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006500664,"about_ca_topic_score_gemma":0.001536806,"domain_scores_codex":[0.9999239,0.00000572506,0.000004031734,0.00001954218,0.00002534438,0.00002136567],"domain_scores_gemma":[0.9999801,0.00000456394,0.000004084034,0.000002379458,0.000005899507,0.000003106922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006161152,0.00005238015,0.00002389502,0.0001161566,0.000007939248,0.00004558211,0.00002183073,0.00038484,0.9799163,0.0009597259,0.0009336484,0.01747611],"study_design_scores_gemma":[0.000009679789,0.0001010881,0.0002005974,0.000007734393,0.00001125093,0.00005259151,0.0000154668,0.004276092,0.9841097,0.0002256786,0.01098334,0.000006758659],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"other","genre_scores_codex":[0.842144,0.04642976,0.04099538,0.001166153,0.001489135,0.0001760996,0.0003715376,0.001104438,0.06612363],"genre_scores_gemma":[0.959996,0.008323957,0.01097242,0.0002293871,0.00009024142,0.00006847995,0.0001469907,0.00007069593,0.02010185],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.001162744,"threshold_uncertainty_score":0.00388974,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005657034599875416,"score_gpt":0.2191801459602945,"score_spread":0.2135231113604191,"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."}}