{"id":"W2095923908","doi":"10.1016/j.jprocont.2003.09.009","title":"Closed-loop identification via output fast sampling","year":2003,"lang":"en","type":"article","venue":"Journal of Process Control","topic":"Control Systems and Identification","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Bispectrum; Identifiability; Control theory (sociology); Closed loop; Sampling (signal processing); Identification (biology); System identification; SIGNAL (programming language); Loop (graph theory); Computer science; Linear system; Mathematics; Control engineering; Engineering; Artificial intelligence; Statistics; Data mining; Machine learning","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":[0.001052552,0.0006732704,0.0007567335,0.000374752,0.0004812752,0.0009298398,0.0004300667,0.0005413943,0.001992739],"category_scores_gemma":[0.004184635,0.0003255817,0.0002644707,0.0004191571,0.0004112269,0.001051447,0.0008456671,0.00085567,0.0003801309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000313455,"about_ca_system_score_gemma":0.0005109074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001278746,"about_ca_topic_score_gemma":0.001479311,"domain_scores_codex":[0.9993441,0.0002003886,0.00003905173,0.00008441635,0.0002791286,0.00005297018],"domain_scores_gemma":[0.9981899,0.00109279,0.0001086076,0.0002494548,0.0003349886,0.00002429462],"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":[0.003277382,0.000220514,0.002455594,0.0006567583,0.0001451526,0.0003720069,0.0006006839,0.1314655,0.1189104,0.03403437,0.001668391,0.7061932],"study_design_scores_gemma":[0.0000984193,0.0002041946,0.0013227,0.00003291177,0.00003172111,0.0001554042,0.00002396992,0.9543341,0.03630955,0.005013112,0.002449898,0.00002403573],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0252183,0.000169956,0.9717864,0.00006607543,0.00006091539,0.00003826331,0.00004177321,0.0008073558,0.00181091],"genre_scores_gemma":[0.8344982,0.0001779186,0.1621103,0.00006620475,0.00005277891,0.00008726736,0.0001193045,0.0001244993,0.002763476],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001992739,"threshold_uncertainty_score":0.006666362,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01147842556218422,"score_gpt":0.2364856993374864,"score_spread":0.2250072737753021,"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."}}