{"id":"W2001806726","doi":"10.4271/2014-01-0052","title":"A New Adaptive Controller for Performance Improvement of Automotive Suspension Systems with MR Dampers","year":2014,"lang":"en","type":"article","venue":"SAE International Journal of Passenger Cars - Mechanical Systems","topic":"Vibration Control and Rheological Fluids","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Damper; Automotive industry; Suspension (topology); Automotive engineering; Computer science; Controller (irrigation); Control engineering; Engineering; Control theory (sociology); Aerospace engineering; Artificial intelligence; Control (management); Mathematics","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":[0.0003064139,0.0004813479,0.0003393497,0.0003409825,0.0002721853,0.0004460177,0.0008925888,0.0004418662,0.002096186],"category_scores_gemma":[0.000418349,0.0001299255,0.0002633807,0.0001973387,0.0002354777,0.0002796753,0.0003511944,0.0004610652,0.0004565502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002015867,"about_ca_system_score_gemma":0.0002136927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001217342,"about_ca_topic_score_gemma":0.001230521,"domain_scores_codex":[0.9997978,0.00002784958,0.00001666549,0.00005180969,0.00008891102,0.00001699279],"domain_scores_gemma":[0.9998373,0.00003904563,0.00002384302,0.00001289504,0.0000778896,0.000009093498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004680126,0.0001686977,0.0005849365,0.0006086231,0.0001169413,0.0002655806,0.0002832977,0.1442336,0.2700793,0.006291663,0.003732072,0.5731671],"study_design_scores_gemma":[0.00008913861,0.0006720651,0.0009539244,0.00003269991,0.00005121207,0.0001516387,0.00002329908,0.9652395,0.02168902,0.0005237616,0.01054225,0.0000315235],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02911632,0.0007916147,0.9624116,0.00009594295,0.0002099437,0.00008902531,0.00002224875,0.001208045,0.006055168],"genre_scores_gemma":[0.8742577,0.0004254592,0.1171691,0.0001358709,0.0001937626,0.0001935396,0.00006931926,0.00006628609,0.007488987],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002096186,"threshold_uncertainty_score":0.007012427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009317020699807464,"score_gpt":0.2093713181512242,"score_spread":0.2000542974514167,"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."}}