{"id":"W4240685246","doi":"10.1142/s0218126609005496","title":"OPTIMAL ADAPTIVE PREDICTION FOR SISO SYSTEMS","year":2009,"lang":"en","type":"article","venue":"Journal of Circuits Systems and Computers","topic":"Control Systems and Identification","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Control theory (sociology); Mathematics; White noise; Perturbation (astronomy); LTI system theory; Minimum mean square error; Adaptive control; Asymptotically optimal algorithm; Mean squared prediction error; Mean square; Mathematical optimization; Applied mathematics; Linear system; Computer science; Statistics; 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":[0.0004138561,0.000373409,0.0005583381,0.0001922202,0.0002373457,0.0005181086,0.0002658838,0.0004729658,0.001186597],"category_scores_gemma":[0.001924973,0.0002524829,0.0001601068,0.0003738885,0.0005004763,0.0005113271,0.0005332842,0.0006825579,0.0002325722],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003208444,"about_ca_system_score_gemma":0.0007622264,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003768194,"about_ca_topic_score_gemma":0.003142643,"domain_scores_codex":[0.999699,0.00006242719,0.0000152957,0.00006374234,0.0001192277,0.00004048095],"domain_scores_gemma":[0.9996163,0.0002216447,0.00003815988,0.00002654905,0.00008505974,0.00001231802],"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":[0.0001269377,0.00002367756,0.000503482,0.0001186354,0.00002404098,0.00009805665,0.00007553292,0.9050659,0.004017203,0.02507102,0.001599275,0.0632763],"study_design_scores_gemma":[0.000007429921,0.00001495243,0.0001257591,0.000006765368,0.000003108298,0.000008076525,0.000004131712,0.9936596,0.0004587705,0.005351462,0.0003555331,0.000004438919],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0296257,0.001526682,0.9623592,0.0003372658,0.0001297974,0.00002433234,0.00007345418,0.0003353547,0.005588238],"genre_scores_gemma":[0.9613644,0.0009221446,0.03410473,0.00009965651,0.00008197474,0.00005912714,0.00008673067,0.00002361642,0.003257594],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003768194,"threshold_uncertainty_score":0.007492542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01174603948599846,"score_gpt":0.1950458639401343,"score_spread":0.1832998244541359,"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."}}