{"id":"W2894788163","doi":"10.1016/j.sigpro.2018.09.040","title":"Modeling of multiple-input, time-varying systems with recursively estimated basis expansions","year":2018,"lang":"en","type":"article","venue":"Signal Processing","topic":"Control Systems and Identification","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Hyperparameter; Estimator; Kalman filter; Computer science; Algorithm; Computation; Nonlinear system; Recursive least squares filter; Mathematical optimization; Mathematics; Adaptive filter; Artificial intelligence; Statistics","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":[0.0003260569,0.0004408363,0.0005664153,0.0002406371,0.0001914461,0.0005518416,0.0006663352,0.0008291961,0.000725597],"category_scores_gemma":[0.001081383,0.0003224267,0.0004934631,0.0002993722,0.0003190569,0.00062575,0.0004013964,0.0007964073,0.0002194745],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003177838,"about_ca_system_score_gemma":0.0005121758,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004009339,"about_ca_topic_score_gemma":0.005157766,"domain_scores_codex":[0.9998343,0.00005590868,0.000007192986,0.0000260841,0.00005525201,0.00002127266],"domain_scores_gemma":[0.9997417,0.0001347716,0.00004602231,0.00002548029,0.00004192122,0.00001007184],"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":[0.00002863363,0.00001381235,0.0001963695,0.00002231032,0.00001828429,0.00003488056,0.0000320635,0.9788824,0.00371781,0.006879078,0.0001256349,0.01004876],"study_design_scores_gemma":[8.001034e-7,0.000003348523,0.00004128056,0.00000107413,0.000001641934,0.000003962728,0.000001147529,0.9993344,0.0001766901,0.0003815493,0.00005275571,0.000001323419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04679871,0.0002347013,0.9510125,0.00009558204,0.00002835601,0.00001258103,0.0000386886,0.0001765292,0.001602441],"genre_scores_gemma":[0.9164285,0.0004339228,0.07838153,0.00003191998,0.00003075604,0.00006677848,0.0001148604,0.00005770043,0.004453831],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004009339,"threshold_uncertainty_score":0.007972002,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0210062687376145,"score_gpt":0.2351338906339744,"score_spread":0.2141276218963599,"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."}}