{"id":"W2799336444","doi":"10.1139/tcsme-2016-0061","title":"PERFORMANCE INVESTIGATION OF AN SI ENGINE WITH VARIABLE VALVE TIMING AND LIFT BASED ON A MAGNETO-RHEOLOGICAL VALVE","year":2016,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Iterative Learning Control Systems","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Valve timing; Lift (data mining); Torque; Valve actuator; Four-stroke engine; Volumetric efficiency; Needle valve; Cylinder; Globe valve; Mechanical engineering; Materials science; Automotive engineering; Mechanics; Ball valve; Control theory (sociology); Engineering; Computer science; Internal combustion engine; Physics; Combustion chamber; Combustion; Chemistry","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0003774599,0.000336265,0.0004580126,0.0003702611,0.0002972134,0.0003433149,0.0005400952,0.0003062924,0.0006341215],"category_scores_gemma":[0.0004524594,0.0002015899,0.0003700702,0.000194667,0.0003157917,0.000367044,0.000268823,0.0002397742,0.0001382558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002438117,"about_ca_system_score_gemma":0.0003242828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002045847,"about_ca_topic_score_gemma":0.001625166,"domain_scores_codex":[0.9998035,0.00002157192,0.00001490662,0.00003299782,0.00008700071,0.00004002076],"domain_scores_gemma":[0.9997407,0.00006403527,0.00003390147,0.00003209539,0.00008856256,0.0000408279],"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":[0.001668623,0.000218256,0.00734437,0.0003490595,0.000074982,0.0003184736,0.0001893926,0.0403503,0.9278862,0.0007722438,0.0002787017,0.0205494],"study_design_scores_gemma":[0.0001528847,0.003597321,0.02198929,0.0000180002,0.0001135237,0.0002483083,0.0001658097,0.4669475,0.5048295,0.0001653711,0.001696206,0.00007627489],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9952359,0.0001120445,0.003564832,0.00002661521,0.00001929205,0.000008258953,0.00002973865,0.0001103885,0.0008929423],"genre_scores_gemma":[0.9989304,0.00003657757,0.0007622179,0.000002992522,0.000001678952,0.000002906391,0.00002345535,0.0000045067,0.0002351285],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002045847,"threshold_uncertainty_score":0.004067898,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00808371709019157,"score_gpt":0.1739521482342652,"score_spread":0.1658684311440736,"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."}}