{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001859949,0.0001502669,0.000241155,0.0001247148,0.0001690408,0.00009262627,0.0001105545,0.00006725478,0.00001466201],"category_scores_gemma":[0.00002359484,0.0001323616,0.00003173782,0.0002919252,0.00003920473,0.0003270317,0.00001292642,0.00009069003,0.00002638136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005004458,"about_ca_system_score_gemma":0.00004651044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001344759,"about_ca_topic_score_gemma":0.00001040298,"domain_scores_codex":[0.9989862,0.00002296497,0.0003627072,0.0001968092,0.0002105668,0.0002206913],"domain_scores_gemma":[0.9993272,0.00003310422,0.00008796666,0.0001437995,0.0003459604,0.00006199475],"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":[0.00004224713,0.0000189866,0.0002383796,0.0004664554,0.00004800235,0.000002082755,0.0009141322,0.7367105,0.2488518,0.000008859573,0.00005456191,0.01264393],"study_design_scores_gemma":[0.0003280738,0.00003860269,0.00005808542,0.001306815,0.00003653756,0.00001020883,0.0001748352,0.9914848,0.006365477,0.0000136234,0.00001809722,0.0001648231],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4025377,0.001434816,0.593422,0.00001305791,0.0001346863,0.0003163602,0.00001010072,0.0003616573,0.001769608],"genre_scores_gemma":[0.997988,0.00000320531,0.001707263,0.000003185947,0.0001602934,0.00002506386,0.00001008717,0.00004364588,0.00005923106],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5954503,"threshold_uncertainty_score":0.5397551,"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."}}