{"id":"W2290746827","doi":"10.4271/2016-01-0815","title":"Innovative Exergy-Based Combustion Phasing Control of IC Engines","year":2016,"lang":"en","type":"article","venue":"SAE technical papers on CD-ROM/SAE technical paper series","topic":"Advanced Combustion Engine Technologies","field":"Chemical Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Alberta","keywords":"Automotive engineering; Combustion; Phaser; Control (management); Computer science; Environmental science; Engineering; Chemistry; Electrical engineering; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003578305,0.00043709,0.0003313563,0.0003482669,0.000178805,0.0005776742,0.0005947803,0.0002066062,0.0005373614],"category_scores_gemma":[0.0003232716,0.0001927807,0.0002552076,0.0002367582,0.0003185096,0.0003085539,0.0003243499,0.0003263673,0.000105992],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004034346,"about_ca_system_score_gemma":0.0003747706,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002129784,"about_ca_topic_score_gemma":0.002014189,"domain_scores_codex":[0.9998822,0.00001743882,0.00000632289,0.00002152069,0.0000577886,0.00001462651],"domain_scores_gemma":[0.9998959,0.00003366562,0.00002576444,0.000009034075,0.00002958089,0.000006092822],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001605995,0.0001012189,0.0006617046,0.0001305619,0.00003344662,0.00005465212,0.00006746776,0.8182761,0.06878138,0.006926485,0.0003850147,0.1044214],"study_design_scores_gemma":[0.00000635987,0.00005012148,0.0002544976,0.00000400021,0.000006816667,0.000008061511,0.000004319071,0.9855798,0.01299347,0.0005139375,0.0005723136,0.000006175784],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08657014,0.0003773113,0.9055636,0.00005739513,0.00002948377,0.00006092567,0.00002880668,0.000376533,0.00693576],"genre_scores_gemma":[0.9507824,0.0001513834,0.04718755,0.00001787234,0.00001065858,0.00004739604,0.00003908613,0.00003543788,0.001728404],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002129784,"threshold_uncertainty_score":0.004234791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01077350188313163,"score_gpt":0.2427387181876092,"score_spread":0.2319652163044775,"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."}}