{"id":"W4403016568","doi":"10.1016/j.cej.2024.156343","title":"Efficient nitrate electroreduction to ammonia over copper catalysts supported on electron-delocalized covalent organic frameworks","year":2024,"lang":"en","type":"article","venue":"Chemical Engineering Journal","topic":"Ammonia Synthesis and Nitrogen Reduction","field":"Chemical Engineering","cited_by":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Fundamental Research Funds for the Central Universities; China Postdoctoral Science Foundation; Natural Science Foundation of Jiangsu Province; National Natural Science Foundation of China","keywords":"Delocalized electron; Catalysis; Copper; Nitrate; Ammonia; Covalent bond; Inorganic chemistry; Chemistry; Ammonia production; Organic 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002890372,0.0004425976,0.000405516,0.0003246648,0.00008920863,0.0001864697,0.0002556831,0.0004336976,0.000230115],"category_scores_gemma":[0.0002500847,0.0004025006,0.0002912938,0.0007303392,0.00002722233,0.00007906546,0.00004427882,0.002215244,0.0002292655],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009050061,"about_ca_system_score_gemma":0.0001108913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004994956,"about_ca_topic_score_gemma":1.600623e-7,"domain_scores_codex":[0.9975078,0.0000198266,0.000571939,0.0005115904,0.0005432377,0.0008456543],"domain_scores_gemma":[0.9989265,0.0001158178,0.00006118586,0.0002791389,0.00009209623,0.0005252578],"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":[0.0001030432,0.00008584697,0.000002879762,0.0000602594,0.0001931444,0.00004882858,0.00009863805,0.06073361,0.9343569,0.0004254227,0.002804876,0.001086498],"study_design_scores_gemma":[0.0002749338,0.00006922144,0.00001876253,0.0003138331,0.00008833977,0.0005170407,0.00001055831,0.1686791,0.8279524,0.0000301799,0.001640612,0.0004049948],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9327337,0.00104873,0.06373887,0.000550106,0.001097952,0.0001922984,0.000007471308,0.000556963,0.00007396688],"genre_scores_gemma":[0.9952974,0.00003201647,0.003005442,0.00008337692,0.00124189,0.00003260862,0.00002086303,0.000154359,0.000131985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1079455,"threshold_uncertainty_score":0.9998427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005155862587274407,"score_gpt":0.2267249053867418,"score_spread":0.2215690427994673,"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."}}