{"id":"W2785983933","doi":"10.1115/1.4039152","title":"Switching Gain-Scheduled Proportional–Integral–Derivative Electronic Throttle Control for Automotive Engines","year":2018,"lang":"en","type":"article","venue":"Journal of Dynamic Systems Measurement and Control","topic":"Extremum Seeking Control Systems","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; SNC-Lavalin (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"PID controller; Throttle; Control theory (sociology); Automotive industry; Controller (irrigation); Computer science; Automotive engineering; Control engineering; Engineering; Control (management); Temperature control","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002987115,0.0003924572,0.0009663137,0.0002685579,0.0001703124,0.0001432699,0.0002488296,0.0001471138,0.000006390026],"category_scores_gemma":[0.0004079855,0.0003100897,0.000264644,0.000141815,0.00005827473,0.0003100579,0.000007991501,0.0003448066,0.000005036538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007359141,"about_ca_system_score_gemma":0.0002094346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002204373,"about_ca_topic_score_gemma":0.0000715876,"domain_scores_codex":[0.9969546,0.0001854011,0.001196761,0.0002448699,0.0008096953,0.0006086853],"domain_scores_gemma":[0.9967065,0.0002260034,0.0006923354,0.0002035202,0.002014666,0.0001569779],"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":[0.001212797,0.0001958761,0.002710382,0.0008720751,0.006890025,0.00002051214,0.002199195,0.009111924,0.9660863,0.003495391,0.0009048217,0.006300723],"study_design_scores_gemma":[0.0114717,0.001072842,0.001765711,0.0009021784,0.0004670321,0.0001784865,0.0006345392,0.9805779,0.0003552658,0.0006362328,0.001475421,0.0004626423],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0456462,0.008256939,0.941426,0.0003494197,0.002153532,0.001786461,0.00001988607,0.0001455369,0.0002160631],"genre_scores_gemma":[0.9982772,0.00003171559,0.0001925102,0.00005473034,0.001186001,0.0001334593,0.000001696753,0.00007245898,0.00005024061],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.971466,"threshold_uncertainty_score":0.9999351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009285156689047737,"score_gpt":0.2150073943014799,"score_spread":0.2057222376124321,"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."}}