{"id":"W2180149114","doi":"10.1016/s0005-1098(03)00090-6","title":"Limiting performance of optimal linear discrete filters","year":2003,"lang":"en","type":"article","venue":"Automatica","topic":"Control Systems and Identification","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Control theory (sociology); Mathematics; Noise (video); Transmission (telecommunications); Filter (signal processing); Dimension (graph theory); Limiting; Zero (linguistics); Discrete time and continuous time; Statistics; Mathematical analysis; Computer science; Engineering; Telecommunications","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":[0.002137403,0.0008560887,0.0007025412,0.0005208572,0.0004772568,0.002925622,0.0006314089,0.001559596,0.003503805],"category_scores_gemma":[0.0136479,0.0004615588,0.0002844651,0.0004463596,0.001812474,0.002023799,0.001218471,0.0009850806,0.0009178442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001138931,"about_ca_system_score_gemma":0.0007245188,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001207583,"about_ca_topic_score_gemma":0.0004607323,"domain_scores_codex":[0.9985822,0.0003867535,0.00005973255,0.0001940424,0.0005437664,0.0002333941],"domain_scores_gemma":[0.9926382,0.005635363,0.0004204764,0.0005571632,0.0005873599,0.0001614699],"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":[0.00207377,0.0002550106,0.001664948,0.0005732166,0.0001010647,0.0002609953,0.0005681308,0.5375081,0.06996323,0.2347068,0.00259825,0.1497265],"study_design_scores_gemma":[0.00006165845,0.0001569588,0.0004868012,0.00003855331,0.00002980127,0.0001038507,0.00007195292,0.905677,0.02667934,0.06507155,0.001586088,0.00003632409],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1815426,0.001505812,0.7874747,0.0008092637,0.0001535469,0.00003046766,0.00006144004,0.0008965719,0.02752559],"genre_scores_gemma":[0.9716784,0.000666698,0.02117462,0.0001270495,0.0001057377,0.00004016924,0.00006978794,0.00009074527,0.006046792],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003503805,"threshold_uncertainty_score":0.01172137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007275777251321337,"score_gpt":0.1980830373887023,"score_spread":0.190807260137381,"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."}}