{"id":"W2284343672","doi":"10.1016/j.ijhydene.2015.11.119","title":"Nitrogen and sulfur co-doped mesoporous carbon as cathode catalyst for H2/O2 alkaline membrane fuel cell – effect of catalyst/bonding layer loading","year":2016,"lang":"en","type":"article","venue":"International Journal of Hydrogen Energy","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":20,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Donghua University; National Natural Science Foundation of China","keywords":"Catalysis; Cathode; Chemical engineering; Carbon fibers; Materials science; Mesoporous material; Power density; Sulfur; Membrane electrode assembly; Direct-ethanol fuel cell; Inorganic chemistry; Chemistry; Electrode; Proton exchange membrane fuel cell; Composite material; Electrolyte; Metallurgy; Organic chemistry; Composite number; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001808506,0.0002775902,0.0003128442,0.0003323824,0.0002946353,0.0003433679,0.0004699619,0.0005313554,0.001342364],"category_scores_gemma":[0.0002235146,0.0001674224,0.0002497742,0.0001890918,0.0001407861,0.0004327334,0.0001814359,0.000264284,0.0002579816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003575161,"about_ca_system_score_gemma":0.0003147499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00329831,"about_ca_topic_score_gemma":0.01229837,"domain_scores_codex":[0.9998755,0.00001054349,0.00001068957,0.00002354642,0.00005173555,0.00002788197],"domain_scores_gemma":[0.9999092,0.00001528948,0.000009119685,0.000005909663,0.00003702187,0.00002338372],"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":[0.0005411709,0.00005694036,0.0002954592,0.0001101266,0.00001585603,0.0001070903,0.00002288975,0.0003359098,0.9946452,0.0001117491,0.0001521098,0.003605385],"study_design_scores_gemma":[0.00001199566,0.0002165799,0.001658169,0.000006002777,0.00001981698,0.00005380719,0.00003765367,0.00177731,0.9954371,0.00002953639,0.0007444529,0.000007596375],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969717,0.001044697,0.0003844505,0.00004959307,0.00004513683,0.000009176307,0.0001378282,0.00002941693,0.001328004],"genre_scores_gemma":[0.9979658,0.0003975676,0.0003092186,0.00001041688,0.000005885619,0.000003749028,0.000117455,0.000006854186,0.001183181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00329831,"threshold_uncertainty_score":0.006558239,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00815534451349406,"score_gpt":0.2503948542372393,"score_spread":0.2422395097237453,"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."}}