{"id":"W2590755368","doi":"10.1016/j.carbon.2017.02.056","title":"Heavily nitrogen-doped acetylene black as a high-performance catalyst for oxygen reduction reaction","year":2017,"lang":"en","type":"article","venue":"Carbon","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":42,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Education Department of Sichuan Province; Sichuan University of Science and Engineering; China Scholarship Council; University of Waterloo","keywords":"Acetylene; Catalysis; Carbon black; Ammonia; Nitrogen; Inorganic chemistry; Chemistry; Graphene; Oxidizing agent; Oxygen; Doping; Materials science; Organic chemistry; Nanotechnology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002962409,0.0002723915,0.0002965401,0.0001400422,0.0005051983,0.00008301222,0.000443053,0.000225318,0.00001219626],"category_scores_gemma":[0.0001449896,0.0002826109,0.0001269865,0.0001177643,0.0001262569,0.0005050844,0.00008863642,0.0001872136,0.00012215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004901023,"about_ca_system_score_gemma":0.0001178122,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007871948,"about_ca_topic_score_gemma":0.0003816252,"domain_scores_codex":[0.9983288,0.00003203567,0.0002940125,0.0005323039,0.0003318416,0.000480999],"domain_scores_gemma":[0.9980845,0.00002074159,0.0003379068,0.001188617,0.0002411763,0.0001270823],"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":[0.000560786,0.00005881939,0.0002136001,0.00006790623,0.0001395305,0.000004060948,0.0001603168,0.0004238411,0.9858841,0.003243443,0.0004515761,0.008791999],"study_design_scores_gemma":[0.001444708,0.0003130635,0.001190232,0.00005086126,0.0001413296,0.00004231699,0.00006632307,0.001864291,0.9788156,0.001247908,0.01444609,0.0003772476],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9808804,0.00008250504,0.00001710995,0.0005404484,0.0009601245,0.000299331,0.000002092067,0.0001916636,0.01702632],"genre_scores_gemma":[0.994548,0.0001268083,0.0001830757,0.00005068587,0.0008295553,0.0001047217,0.0002223408,0.00008056518,0.003854258],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01399452,"threshold_uncertainty_score":0.9999626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0123845471808858,"score_gpt":0.2374717877010907,"score_spread":0.2250872405202049,"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."}}