{"id":"W2148335298","doi":"10.1149/1.1781611","title":"Fe-Based Catalysts for Oxygen Reduction in PEM Fuel Cells","year":2004,"lang":"en","type":"article","venue":"Journal of The Electrochemical Society","topic":"Electrocatalysts for Energy Conversion","field":"Energy","cited_by":127,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Catalysis; Proton exchange membrane fuel cell; Carbon black; Carbon fibers; Electrochemistry; Chemistry; Electrolyte; Inorganic chemistry; Oxygen; Direct-ethanol fuel cell; Catalyst support; Chemical engineering; Materials science; Electrode; Organic chemistry; Composite material","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":[],"consensus_categories":[],"category_scores_codex":[0.0005013105,0.0001882868,0.0002937496,0.00005229262,0.0001018792,0.00002207124,0.0005247059,0.0002198572,0.000005846203],"category_scores_gemma":[0.0001062706,0.0001386091,0.0008150255,0.0004909124,0.00007027964,0.0001506086,0.00003908165,0.0005660892,0.000003785252],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001652081,"about_ca_system_score_gemma":0.0004184745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009912098,"about_ca_topic_score_gemma":0.0000521787,"domain_scores_codex":[0.9983469,0.00003848988,0.0004843849,0.0002020415,0.0004767219,0.0004514602],"domain_scores_gemma":[0.9989306,0.00006871014,0.0004004458,0.0002502546,0.0002487983,0.0001011416],"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":[0.0001938606,0.000138194,0.00001190866,0.00003433421,0.00008267661,0.000001063487,0.0002158711,0.001306049,0.9957041,0.000425027,0.001719273,0.0001676761],"study_design_scores_gemma":[0.002285905,0.0001508821,0.00004242484,0.00005602982,0.00007733236,0.00005646004,0.00006351493,0.0001512241,0.9835469,0.01067459,0.002736897,0.0001578354],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9759769,0.0008930949,0.01058226,0.01103177,0.0007447483,0.0003394067,0.000001325375,0.0000528288,0.0003776931],"genre_scores_gemma":[0.9910177,0.00005190958,0.00781491,0.0004576026,0.0004457734,0.00000912311,0.000008734562,0.00003511573,0.0001591211],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01504084,"threshold_uncertainty_score":0.5652316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006732921268656301,"score_gpt":0.2166493338010174,"score_spread":0.2099164125323611,"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."}}