{"id":"W4388571030","doi":"10.1002/smll.202307011","title":"Concave Structural Carbon Co‐Doped with Iron Atom Pairs and Nitrogen as Ultra‐High Performance Catalyst Toward Oxygen Reduction","year":2023,"lang":"en","type":"article","venue":"Small","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Catalysis; Electrocatalyst; Proton exchange membrane fuel cell; X-ray photoelectron spectroscopy; X-ray absorption spectroscopy; Carbon fibers; Inorganic chemistry; Transition metal; Chemistry; Oxygen; Materials science; Absorption spectroscopy; Physical chemistry; Electrochemistry; Chemical engineering; Electrode; Organic 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001763828,0.0002993933,0.0002804838,0.0001833827,0.000179669,0.0000421696,0.0002058694,0.0001554414,0.00003820691],"category_scores_gemma":[0.00001623974,0.0002591029,0.00004936835,0.0004651787,0.0001399671,0.0001846307,0.00005202864,0.0002220249,0.0001047788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002115898,"about_ca_system_score_gemma":0.000106897,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009003214,"about_ca_topic_score_gemma":0.0007547989,"domain_scores_codex":[0.9982891,0.00006025603,0.0002379823,0.0005325011,0.0003586281,0.0005215008],"domain_scores_gemma":[0.9992047,0.00003016268,0.0001221205,0.0003835779,0.0001057967,0.0001536357],"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":[0.003281295,0.00008462054,0.07616025,0.0008583799,0.001354496,0.0003850271,0.01156028,0.01335115,0.8516377,0.009380489,0.001068876,0.03087749],"study_design_scores_gemma":[0.002133138,0.0007993652,0.01939275,0.00006489802,0.000198418,0.0003606059,0.001290294,0.002000582,0.969761,0.0005371564,0.002668777,0.000792988],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9943358,0.00009973579,0.000001748467,0.0002021174,0.0002018391,0.000182785,0.000003949752,0.0003930089,0.00457906],"genre_scores_gemma":[0.9975063,0.0001127951,0.00008238674,0.00004309788,0.0001987107,0.00002928704,0.0005138989,0.00007132967,0.001442224],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1181234,"threshold_uncertainty_score":0.9999861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0101439270851007,"score_gpt":0.2068124350936371,"score_spread":0.1966685080085364,"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."}}