{"id":"W2945075429","doi":"10.1021/acsenergylett.9b00975","title":"CO <sub>2</sub> Electroreduction from Carbonate Electrolyte","year":2019,"lang":"en","type":"article","venue":"ACS Energy Letters","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":260,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institute for Advanced Research","keywords":"Syngas; Electrolysis; Electrolyte; Carbonate; Electrochemistry; Chemical engineering; Catalysis; Upgrade; Chemistry; Materials science; Waste management; Electrode; Organic chemistry; Computer science; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001226573,0.0004319524,0.000186852,0.0002117573,0.00025333,0.0004621831,0.0003884079,0.0003173239,0.001128485],"category_scores_gemma":[0.000243715,0.0001358616,0.0001598045,0.0002413253,0.0002172006,0.0004231064,0.0002644667,0.0005293369,0.0004365472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003900634,"about_ca_system_score_gemma":0.0002685929,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001103855,"about_ca_topic_score_gemma":0.003736017,"domain_scores_codex":[0.9998149,0.000008537669,0.0000122322,0.00004699293,0.00008713349,0.00003017263],"domain_scores_gemma":[0.9999064,0.00001834078,0.00001498017,0.0000117875,0.00003706656,0.00001131357],"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":[0.0000453591,0.00001757046,0.0003873136,0.0000967063,0.000008127879,0.00008717685,0.00001416272,0.0001102405,0.9920198,0.0004614946,0.0002645655,0.006487386],"study_design_scores_gemma":[0.00000200243,0.00003348519,0.0004212871,0.000001371558,0.000002874247,0.00009466959,0.00000669624,0.0005336731,0.9967,0.00002536955,0.002176146,0.00000244172],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9297125,0.002842861,0.04148746,0.0006917609,0.0004357852,0.0001182867,0.0004854382,0.0006701389,0.02355582],"genre_scores_gemma":[0.9826092,0.0009692704,0.01173183,0.0001074125,0.00003237242,0.00002036196,0.0002248429,0.0000632654,0.004241537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001128485,"threshold_uncertainty_score":0.003775179,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003870545469062706,"score_gpt":0.1927894274187706,"score_spread":0.1889188819497079,"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."}}