{"id":"W2064176571","doi":"10.1007/s11244-009-9361-7","title":"Global Kinetic Model and Parameter Optimization for a Diesel Oxidation Catalyst","year":2009,"lang":"en","type":"article","venue":"Topics in Catalysis","topic":"Catalytic Processes in Materials Science","field":"Materials Science","cited_by":34,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Kinetic energy; Catalysis; Ignition system; Extension (predicate logic); Diesel fuel; Variety (cybernetics); Biological system; Reduction (mathematics); Chemistry; Computer science; Thermodynamics; Mathematics; Physics; Organic chemistry; Geometry; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0004202515,0.0001399092,0.0002319257,0.00008501705,0.00008636729,0.0001600806,0.0002984973,0.00007488461,0.00003005729],"category_scores_gemma":[0.0004545456,0.000134288,0.00003560125,0.0003601777,0.0001022149,0.0003872749,0.00007786167,0.00002965185,0.000006371471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001246881,"about_ca_system_score_gemma":0.00005054974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006497559,"about_ca_topic_score_gemma":0.00006679018,"domain_scores_codex":[0.9987295,0.00001663381,0.0003319037,0.000442087,0.0002123169,0.0002675177],"domain_scores_gemma":[0.9993375,0.00005505793,0.0001124984,0.0003495429,0.00008600031,0.0000594357],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001519055,0.0002830093,0.0013503,0.0002391527,0.00001402149,0.000006695007,0.001217962,0.7653016,0.2031754,0.009986374,0.0003150917,0.01795853],"study_design_scores_gemma":[0.0006740444,0.0000928544,0.00197566,0.00003656246,0.00008629915,0.00001464135,0.00005434743,0.8916606,0.06601307,0.03891229,0.00008396207,0.0003956726],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.811226,0.00009934897,0.1874019,0.0005260559,0.0001328084,0.000259172,0.00004223797,0.00004840247,0.0002640983],"genre_scores_gemma":[0.9319385,0.00002562936,0.06757061,0.0001885996,0.00005521647,0.00004476966,0.00008181934,0.000005449449,0.00008940459],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1371623,"threshold_uncertainty_score":0.5476108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01820302805584519,"score_gpt":0.2843464893067606,"score_spread":0.2661434612509154,"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."}}