{"id":"W2810227774","doi":"10.1016/j.jcis.2018.06.073","title":"Phosphorus-doped cobalt-iron oxyhydroxide with untrafine nanosheet structure enable efficient oxygen evolution electrocatalysis","year":2018,"lang":"en","type":"article","venue":"Journal of Colloid and Interface Science","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":51,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"Priority Academic Program Development of Jiangsu Higher Education Institutions; National Natural Science Foundation of China","keywords":"Tafel equation; Nanosheet; Overpotential; Oxygen evolution; Electrocatalyst; Cobalt; Materials science; Water splitting; Chemical engineering; Nanotechnology; Doping; Catalysis; Inorganic chemistry; Chemistry; Electrochemistry; Electrode; Optoelectronics; Physical 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":[],"consensus_categories":[],"category_scores_codex":[0.0007587036,0.0002498406,0.0003606344,0.0004199236,0.0004297749,0.000147494,0.0006612762,0.00008215789,0.00008095372],"category_scores_gemma":[0.0001486905,0.0001767494,0.00007198819,0.00166364,0.0007920699,0.0006453182,0.0001210146,0.0002797373,0.00001300698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007277285,"about_ca_system_score_gemma":0.0006601408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003191313,"about_ca_topic_score_gemma":0.000316095,"domain_scores_codex":[0.9974481,0.00004639938,0.0004544385,0.0003988844,0.001049347,0.0006027831],"domain_scores_gemma":[0.9979345,0.00003291059,0.0004748073,0.0003093877,0.000980444,0.0002679689],"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":[0.0004945584,0.00005316608,0.000192801,0.000008553076,0.00004549644,0.000002416203,0.0003566288,0.006699407,0.9903212,0.001012144,0.0003806848,0.0004329802],"study_design_scores_gemma":[0.000893935,0.002234889,0.0005622662,0.00009726166,0.00008377979,0.0003226068,0.0002852863,0.005565954,0.9843748,0.0002307327,0.00511282,0.0002356323],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949519,0.0008957571,0.001666507,0.0002950994,0.0003152972,0.00009174857,0.000001461756,0.00002536824,0.001756882],"genre_scores_gemma":[0.9983201,0.00006859076,0.0007333384,0.00009461569,0.0001599494,0.000001123265,0.000001303019,0.00001952249,0.0006014436],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005946329,"threshold_uncertainty_score":0.720763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002850661075319569,"score_gpt":0.2066585220691058,"score_spread":0.2038078609937862,"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."}}