{"id":"W4413005560","doi":"10.1039/d5ee02847g","title":"Electrolysis of ethylene to ethylene glycol paired with acidic CO<sub>2</sub>-to-CO conversion","year":2025,"lang":"en","type":"article","venue":"Energy & Environmental Science","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Research Foundation of Korea; Australian Research Council; National Research Foundation; Australian Government","keywords":"Ethylene glycol; Ethylene; Electrolysis; Chemistry; Nuclear chemistry; Organic chemistry; Electrode; Electrolyte; Catalysis","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":[0.0001350516,0.0004295019,0.000345951,0.0002293706,0.0001753139,0.0004434258,0.0004583815,0.0004527891,0.002151912],"category_scores_gemma":[0.000330809,0.0002359366,0.0001791086,0.0002284561,0.0002196931,0.0005287422,0.0004503261,0.0006291122,0.0005759677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002767581,"about_ca_system_score_gemma":0.0002287395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00065334,"about_ca_topic_score_gemma":0.001630376,"domain_scores_codex":[0.9997635,0.00002372726,0.00001268821,0.0000616196,0.00009528161,0.00004320683],"domain_scores_gemma":[0.9999071,0.00002075942,0.00001428309,0.0000122523,0.00002854113,0.00001700266],"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":[0.0002107978,0.0000208141,0.0001906914,0.00006910827,0.000007925996,0.0001144355,0.00001051946,0.00007436996,0.9943975,0.0001967058,0.0001871573,0.004520024],"study_design_scores_gemma":[0.000007269481,0.00004666645,0.0003319485,0.000001955431,0.000006540983,0.00007172073,0.000007310751,0.0007597355,0.9974795,0.00002537356,0.001259613,0.000002383529],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9644952,0.002236035,0.0200862,0.0003475957,0.000376215,0.000117679,0.0002967263,0.0005138001,0.01153056],"genre_scores_gemma":[0.9875922,0.0004762323,0.006627999,0.00007622827,0.00002373442,0.00001407068,0.0001472457,0.00003729563,0.005004918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002151912,"threshold_uncertainty_score":0.00719887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004032490974648782,"score_gpt":0.2141024890816981,"score_spread":0.2100699981070493,"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."}}