{"id":"W2129006067","doi":"10.1109/iembs.1990.692071","title":"Identification Of Multiple Input Wiener Systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Control Systems and Identification","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Medical Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Gaussian; Linearity; Algorithm; Computer science; Nonlinear system; Identification (biology); Linear system; Polynomial; System identification; Control theory (sociology); Mathematics; Artificial intelligence; Electronic engineering; Engineering; Data modeling; Mathematical analysis; Physics","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":[0.000144576,0.00005164668,0.00009141576,0.00006023657,0.00001508282,0.00002840153,0.00006562593,0.00003501947,0.00001834393],"category_scores_gemma":[0.00001491902,0.00004833748,0.0000278261,0.00007984933,0.000006483923,0.0001619424,0.000004699606,0.0000244228,0.0001315725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003227526,"about_ca_system_score_gemma":0.000003032485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008010678,"about_ca_topic_score_gemma":0.00006672867,"domain_scores_codex":[0.9994116,0.000009336126,0.0003358508,0.00007408485,0.00009497118,0.00007414785],"domain_scores_gemma":[0.9996687,0.00001533794,0.00004458844,0.0001951015,0.00005449446,0.00002180781],"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":[0.000002054775,0.00002206597,0.001238075,0.0001083852,0.00002862472,8.322164e-8,0.0001684218,0.1145115,0.8673024,0.002702581,0.004114678,0.009801161],"study_design_scores_gemma":[0.0002292393,0.000003350807,0.007793229,0.00001438307,0.000008003405,0.000001497178,0.00006605207,0.9263126,0.04222332,0.000007786844,0.02325249,0.00008808904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8947614,0.00123914,0.09548399,0.00006933061,0.00105065,0.0003855036,0.00001066997,0.0003595458,0.006639809],"genre_scores_gemma":[0.9974331,0.00001379883,0.00005147864,0.000002403035,0.0001420513,0.00002682098,0.000005402768,0.00001046452,0.002314504],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.825079,"threshold_uncertainty_score":0.1971145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007075237654891104,"score_gpt":0.1929003173041866,"score_spread":0.1858250796492955,"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."}}