{"id":"W2883757223","doi":"10.1007/s41918-018-0014-z","title":"Recent Progresses in Electrocatalysts for Water Electrolysis","year":2018,"lang":"en","type":"article","venue":"Electrochemical Energy Reviews","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":503,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"National Key Research and Development Program of China","keywords":"Noble metal; Electrolysis of water; Electrolysis; Nanotechnology; Electrocatalyst; Materials science; Water splitting; Catalysis; Oxygen evolution; Chemistry; Metal; Metallurgy; Electrochemistry; Electrode","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":[0.0009446426,0.0006854078,0.001139646,0.0004058328,0.0002061771,0.00006036417,0.0008341277,0.0003761594,0.0004517535],"category_scores_gemma":[0.0004546685,0.0005161316,0.0004505476,0.001382121,0.0001773582,0.0002819197,0.0001217591,0.0003772707,0.0002526889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007662755,"about_ca_system_score_gemma":0.0001597864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001467246,"about_ca_topic_score_gemma":0.001594152,"domain_scores_codex":[0.9947717,0.0002160104,0.001174926,0.001229738,0.0005022299,0.002105363],"domain_scores_gemma":[0.9980086,0.0001226973,0.0002361299,0.0009059572,0.0004597791,0.0002668008],"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":[0.0003510993,0.0001860309,0.00001644312,0.00004882966,0.00008698234,0.000003395879,0.00005295331,0.00000171002,0.8920337,0.008800511,0.003436545,0.09498181],"study_design_scores_gemma":[0.0005446625,0.0003759547,0.000001648824,0.00003801849,0.00005472653,0.00002049799,0.000001536149,0.0001786478,0.5175373,0.002334071,0.4785499,0.0003630385],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5295959,0.3141043,0.03813123,0.01310007,0.002212136,0.007295523,0.000007165316,0.00356141,0.09199228],"genre_scores_gemma":[0.9573813,0.0289318,0.002246035,0.002600098,0.001878762,0.002475257,0.00106032,0.0002658013,0.003160589],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4751133,"threshold_uncertainty_score":0.999729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01367609701633499,"score_gpt":0.2608607689966721,"score_spread":0.2471846719803371,"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."}}