{"id":"W2903336990","doi":"10.1016/j.isatra.2018.12.001","title":"Wiener model based GMVC design considering sensor noise and delay","year":2018,"lang":"en","type":"article","venue":"ISA Transactions","topic":"Control Systems and Identification","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Control theory (sociology); Benchmark (surveying); Noise (video); Nonlinear system; Controller (irrigation); Filter (signal processing); Computer science; Engineering; Control engineering; Control (management); Artificial intelligence","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":[0.0004452713,0.0008708311,0.0008389018,0.0003849695,0.0003584247,0.0008937228,0.0007908138,0.001311724,0.002465864],"category_scores_gemma":[0.00111777,0.0003779652,0.0005353255,0.0004483263,0.0003656048,0.0006776946,0.0007270104,0.000690683,0.000802592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004277874,"about_ca_system_score_gemma":0.000880968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002950904,"about_ca_topic_score_gemma":0.00334194,"domain_scores_codex":[0.9996781,0.00006166465,0.00001559607,0.00006741786,0.0001312118,0.00004601723],"domain_scores_gemma":[0.9996791,0.00008238425,0.00003275204,0.00003245594,0.0001590033,0.0000143884],"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":[0.0002047097,0.00007959512,0.0005376231,0.0003246414,0.0001000801,0.0002365558,0.0001494933,0.7188182,0.05946693,0.01985174,0.002547242,0.1976833],"study_design_scores_gemma":[0.00001074714,0.00007932475,0.0001455462,0.00001889579,0.00001863607,0.00007249735,0.000008773339,0.9898703,0.006551339,0.001494676,0.00171746,0.00001192518],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003963663,0.0001736098,0.9932278,0.00005564445,0.00004364814,0.00001884318,0.0000161581,0.0001557839,0.002344995],"genre_scores_gemma":[0.8152634,0.0006529116,0.17413,0.0002276449,0.00009583035,0.0001817694,0.000176499,0.0001324646,0.00913941],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002950904,"threshold_uncertainty_score":0.008249164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0225444058876065,"score_gpt":0.2111895715465972,"score_spread":0.1886451656589907,"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."}}