{"id":"W1511017376","doi":"10.1049/iet-cta.2010.0718","title":"Continuous-time model identification of fractional-order models with time delays","year":2011,"lang":"en","type":"article","venue":"IET Control Theory and Applications","topic":"Advanced Control Systems Design","field":"Engineering","cited_by":101,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Control theory (sociology); Time domain; System identification; Fractional-order system; White noise; Monte Carlo method; Computer science; Mathematics; Noise (video); Applied mathematics; Filter (signal processing); Fractional calculus; Mathematical optimization; Data modeling; Statistics","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":[],"consensus_categories":[],"category_scores_codex":[0.0003464407,0.0001509317,0.0002496861,0.00006286052,0.00008104958,0.00001378786,0.0001313723,0.00007662603,0.00004158905],"category_scores_gemma":[0.00001026724,0.0001394437,0.00003673178,0.000116549,0.00008858489,0.0002804145,0.000007305095,0.00009530719,0.00007090376],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001907108,"about_ca_system_score_gemma":0.00001754384,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002418054,"about_ca_topic_score_gemma":6.117737e-7,"domain_scores_codex":[0.9991538,0.00005477975,0.0003310539,0.0001993122,0.0001060553,0.0001550201],"domain_scores_gemma":[0.9991392,0.0001807895,0.0001236203,0.0003351726,0.0001580468,0.00006317602],"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":[0.0001924993,0.00006504192,0.0000126481,0.00002504116,0.0001838534,3.654889e-7,0.0002385503,0.4889873,0.1133606,0.3936352,0.00004845577,0.003250418],"study_design_scores_gemma":[0.0007849213,0.0000220465,0.00005024501,0.00001083305,0.00009431786,0.000007444764,0.00003472649,0.8223346,0.001537176,0.1747795,0.0001770646,0.0001671584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002759486,0.0003229412,0.9867386,0.00001186451,0.00001021364,0.0007390155,0.00008712472,0.0001982855,0.009132459],"genre_scores_gemma":[0.9952331,0.00001628008,0.002991315,0.00003493779,0.00003911896,0.0008096127,0.00001398466,0.00003705888,0.0008245558],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9924737,"threshold_uncertainty_score":0.5686348,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006800642563255213,"score_gpt":0.1874213979054469,"score_spread":0.1806207553421917,"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."}}