{"id":"W2784943348","doi":"10.1021/acsnano.7b08721","title":"Carbon Nanosheets Containing Discrete Co-N<sub><i>x</i></sub>-B<sub><i>y</i></sub>-C Active Sites for Efficient Oxygen Electrocatalysis and Rechargeable Zn–Air Batteries","year":2018,"lang":"en","type":"article","venue":"ACS Nano","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":483,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Light Source (Canada)","funders":"State Key Laboratory of Inorganic Synthesis and Preparative Chemistry, Jilin University; National Natural Science Foundation of China","keywords":"Catalysis; Electrocatalyst; Electron transfer; Materials science; Carbon fibers; Oxygen evolution; Adsorption; Oxygen; Chemical engineering; Limiting current; Inorganic chemistry; Chemistry; Electrochemistry; Nanotechnology; Physical chemistry; Electrode; Organic chemistry; Composite number","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":[0.00005424088,0.000229487,0.00009734702,0.0001724117,0.0001110166,0.0001782433,0.0002579661,0.000336837,0.0008262734],"category_scores_gemma":[0.0001501658,0.0001406283,0.00009833505,0.000144415,0.0001541751,0.0002193536,0.0001412562,0.0002530125,0.0001624815],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002579557,"about_ca_system_score_gemma":0.0001158248,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007214043,"about_ca_topic_score_gemma":0.002445007,"domain_scores_codex":[0.999939,0.000003366615,0.000005063479,0.00001724218,0.00002284171,0.00001251379],"domain_scores_gemma":[0.9999205,0.00001560278,0.00001929032,0.00001011161,0.00001679858,0.00001767437],"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":[0.00008185399,0.00001959263,0.0001891365,0.00004766035,0.000007191644,0.000062736,0.000009070791,0.0005489425,0.99677,0.0002189017,0.0001105566,0.001934381],"study_design_scores_gemma":[0.00001775708,0.00009471981,0.002303214,0.000004943185,0.00000924813,0.00007502171,0.0000184054,0.003809472,0.9925777,0.00005545307,0.001025715,0.000008417451],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.995414,0.0003252669,0.002179845,0.00003728557,0.00004247099,0.00001745343,0.0001738281,0.00007975478,0.001729974],"genre_scores_gemma":[0.9971889,0.0001235095,0.001750939,0.00001796072,0.000005242944,0.00001562347,0.0001089335,0.00001245006,0.0007765254],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008262734,"threshold_uncertainty_score":0.002764165,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008444256078743679,"score_gpt":0.2230863571685672,"score_spread":0.2146421010898235,"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."}}