{"id":"W2104314578","doi":"","title":"A blind approach to identification of Hammerstein-Wiener systems corrupted by nonlinear-process noise","year":2009,"lang":"en","type":"article","venue":"Asian Control Conference","topic":"Control Systems and Identification","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Nonlinear system; Control theory (sociology); Noise (video); Subspace topology; Parametrization (atmospheric modeling); Mathematics; Inverse; Computer science; Identification (biology); Mathematical analysis; 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":[0.001136957,0.0007993437,0.0009702597,0.0006385549,0.0005301181,0.0007885386,0.0009927847,0.001224254,0.001308971],"category_scores_gemma":[0.002991857,0.0004345597,0.000881749,0.0004089384,0.001223868,0.001742296,0.001585674,0.001296657,0.0004893393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005106148,"about_ca_system_score_gemma":0.001042325,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001173211,"about_ca_topic_score_gemma":0.001246943,"domain_scores_codex":[0.9991358,0.0002324396,0.00005566121,0.0001592655,0.0003681408,0.00004875848],"domain_scores_gemma":[0.9992506,0.0003543882,0.00009042915,0.0001298938,0.0001465123,0.0000282136],"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":[0.0002800147,0.0001339406,0.0008522063,0.0003908059,0.0002068897,0.0002155683,0.0003013356,0.6495217,0.03816485,0.0946008,0.001423928,0.213908],"study_design_scores_gemma":[0.00001007325,0.00005314258,0.0001463942,0.000009620598,0.00001776238,0.00006940081,0.00001056118,0.9731689,0.006847763,0.01825056,0.001387212,0.00002866363],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00177242,0.00007117528,0.9976754,0.00002023692,0.00001739682,0.000007185748,0.000006844641,0.00008727658,0.0003420904],"genre_scores_gemma":[0.3800555,0.0005724721,0.6111482,0.0001233675,0.0001168568,0.0001423789,0.0001166773,0.00009600168,0.007628381],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001308971,"threshold_uncertainty_score":0.006012857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01160228907033732,"score_gpt":0.2257058091247995,"score_spread":0.2141035200544622,"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."}}