{"id":"W2896508033","doi":"10.1002/adma.201804867","title":"A Surface Reconstruction Route to High Productivity and Selectivity in CO<sub>2</sub> Electroreduction toward C<sub>2+</sub> Hydrocarbons","year":2018,"lang":"en","type":"article","venue":"Advanced Materials","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":269,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research; University of Toronto; University of New Brunswick; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Selectivity; Materials science; Catalysis; Faraday efficiency; Electrochemistry; Inorganic chemistry; Current density; Chemical engineering; Copper chloride; Oxide; Ethylene; Copper; Carbon fibers; Electrode; Metallurgy; Composite material; Organic chemistry; Chemistry; Physical chemistry","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":[0.00007287782,0.0003857606,0.0001899076,0.0002032285,0.0001464046,0.0003345473,0.0003358922,0.000221702,0.000613867],"category_scores_gemma":[0.0001306644,0.0001856997,0.0001526811,0.0001797527,0.0002487475,0.0001974943,0.0002311126,0.0003147469,0.0002369606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002887028,"about_ca_system_score_gemma":0.0001493057,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007970363,"about_ca_topic_score_gemma":0.0007641871,"domain_scores_codex":[0.9999313,0.000009614102,0.000003443637,0.00001536074,0.00002228679,0.0000179893],"domain_scores_gemma":[0.9999371,0.00001009341,0.00001808745,0.00001137507,0.00001446468,0.000008942521],"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":[0.00004172995,0.0000180622,0.00008601166,0.00004475211,0.000005422678,0.00006552738,0.00001835641,0.0003930847,0.9948986,0.0005593516,0.0001596559,0.003709409],"study_design_scores_gemma":[0.000007368043,0.00008475201,0.0003971442,0.000001526366,0.000005324843,0.00009631866,0.000009718836,0.002824477,0.9947098,0.00004354181,0.001815117,0.000004943553],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9790161,0.0009485451,0.01444031,0.0001553179,0.00006159784,0.00002711467,0.0001347813,0.0004866713,0.004729616],"genre_scores_gemma":[0.9934967,0.0002377286,0.004800633,0.00001582574,0.000006516258,0.000009957611,0.00007265845,0.0000303937,0.001329505],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007970363,"threshold_uncertainty_score":0.002094746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00858526948151816,"score_gpt":0.2433788448729054,"score_spread":0.2347935753913872,"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."}}