{"id":"W1157126761","doi":"10.1299/jmsesdm.2012.8.251","title":"EC1-1 A Control Strategy Analysis for Clean and Efficient Combustion in Compression Ignition Engines(EC: Engine Control,General Session Papers)","year":2012,"lang":"en","type":"article","venue":"The Proceedings of the International symposium on diagnostics and modeling of combustion in internal combustion engines","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Homogeneous charge compression ignition; Combustion; Automotive engineering; Diesel cycle; Exhaust gas recirculation; Diesel engine; Ignition system; Compression ratio; Internal combustion engine; Diesel fuel; Hydrogen internal combustion engine vehicle; Computer science; Environmental science; Combustion chamber; Engineering; Chemistry; Aerospace engineering","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":[0.0007118946,0.0007211063,0.0003873572,0.000460936,0.0002241266,0.0009663389,0.0003721856,0.0004004868,0.003890323],"category_scores_gemma":[0.0008180591,0.0001321279,0.0005183527,0.000251732,0.0002547547,0.0002879232,0.0002971902,0.0004531174,0.0003393676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000655024,"about_ca_system_score_gemma":0.0006278366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006644335,"about_ca_topic_score_gemma":0.003450084,"domain_scores_codex":[0.9997241,0.00004496501,0.0000157839,0.00003525583,0.0001465276,0.00003333603],"domain_scores_gemma":[0.9997614,0.00009294799,0.00001990519,0.00001922559,0.00009959794,0.000006907826],"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":[0.0002372076,0.0001248526,0.0008708521,0.0004574738,0.00007959762,0.0001561204,0.00005477017,0.8360189,0.04154555,0.01909883,0.002112498,0.09924336],"study_design_scores_gemma":[0.000008004868,0.0001180352,0.0006869242,0.000009823701,0.00001172166,0.00002114578,0.000009770249,0.9893064,0.007159778,0.001382863,0.001279032,0.000006402868],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1342078,0.00253354,0.8037325,0.0002890975,0.0001293856,0.0004023405,0.0002831524,0.0005841327,0.05783813],"genre_scores_gemma":[0.968438,0.0005391309,0.02309389,0.00005857336,0.00002397742,0.000131679,0.000203654,0.00006677293,0.007444365],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006644335,"threshold_uncertainty_score":0.01321131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01491323023434652,"score_gpt":0.2540638142234775,"score_spread":0.239150583989131,"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."}}