{"id":"W2317467614","doi":"10.1115/icef2003-0724","title":"Preliminary Energy-Efficiency Analyses of an Active-Flow Aftertreatment System for Lean-Burn IC Engines","year":2003,"lang":"en","type":"article","venue":"","topic":"Catalytic Processes in Materials Science","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Automotive engineering; Combustion; Energy consumption; Flow (mathematics); Efficient energy use; Lean burn; Internal combustion engine; Environmental science; Monolith; Exhaust gas; Flow control (data); Energy (signal processing); Energy management; Thermal; Energy conservation; Computer science; Engineering; Waste management; Chemistry; Electrical engineering; Mechanics; Telecommunications","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":[0.0003186754,0.0004538296,0.0006840149,0.0004215265,0.0004017682,0.0004023212,0.0005870649,0.0003902179,0.002088197],"category_scores_gemma":[0.0004427063,0.0001633625,0.0003653958,0.0002480115,0.000250371,0.0005285136,0.0001176372,0.0002258645,0.0002935466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005103676,"about_ca_system_score_gemma":0.000246323,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002299383,"about_ca_topic_score_gemma":0.002422407,"domain_scores_codex":[0.999878,0.00001887122,0.00001089438,0.00001657397,0.00004537556,0.00003027095],"domain_scores_gemma":[0.9997537,0.000104252,0.00002534483,0.00002302485,0.0000822279,0.00001150684],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003323426,0.0007147265,0.007720954,0.0008500038,0.000118194,0.000220312,0.0002022073,0.1074571,0.8030422,0.001767598,0.001012678,0.07357061],"study_design_scores_gemma":[0.00005830464,0.001265969,0.005428132,0.000008809353,0.00005379529,0.00003494822,0.00003699342,0.08666215,0.9051026,0.0001515614,0.001177281,0.00001951846],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.985306,0.0002344243,0.01230892,0.00003760908,0.00001026491,0.00007944436,0.0002107108,0.0002721012,0.001540627],"genre_scores_gemma":[0.996927,0.00009534066,0.001700155,0.000007414061,0.000002156004,0.0000190955,0.0001482839,0.00001681579,0.00108378],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002299383,"threshold_uncertainty_score":0.006985664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02641189915134014,"score_gpt":0.2967172248422345,"score_spread":0.2703053256908943,"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."}}