{"id":"W2063777739","doi":"10.1111/j.1934-6093.2001.tb00066.x","title":"Discrete‐Time Risk‐Sensitive Filters with Non‐Gaussian Initial Conditions and Their Ergodic Properties","year":2001,"lang":"en","type":"article","venue":"Asian Journal of Control","topic":"Probabilistic and Robust Engineering Design","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Mathematics; Gaussian; Control theory (sociology); Applied mathematics; Filter (signal processing); Riccati equation; Stability theory; Covariance; Initialization; Mathematical analysis; Statistics; Computer science; Nonlinear system","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":[0.003033491,0.0008353418,0.001173685,0.0009267014,0.0006450985,0.001570799,0.0007855941,0.001394297,0.001938925],"category_scores_gemma":[0.01505456,0.0005831957,0.001077319,0.0004825621,0.002287836,0.001836176,0.001077265,0.001370855,0.0003975787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001732835,"about_ca_system_score_gemma":0.001363088,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004275977,"about_ca_topic_score_gemma":0.001486317,"domain_scores_codex":[0.9987175,0.0002896186,0.00007036209,0.0002614296,0.0004619286,0.00019916],"domain_scores_gemma":[0.9912793,0.004762173,0.001459913,0.000531947,0.001707839,0.0002589209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001083067,0.00004456648,0.00154084,0.00009228694,0.00009140944,0.0002327127,0.000232907,0.759762,0.008261799,0.2170222,0.0003622416,0.01224872],"study_design_scores_gemma":[0.00000823502,0.00004063791,0.0003133974,0.00001187896,0.00001530775,0.00003726948,0.00001660163,0.9793549,0.00239412,0.01754393,0.00024746,0.0000161799],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06558794,0.0001926734,0.9307941,0.0001858337,0.00002327624,0.00002898198,0.0000356112,0.0001047816,0.003046788],"genre_scores_gemma":[0.9625918,0.0003167022,0.03166683,0.00007941543,0.00003121625,0.0001049353,0.00008374618,0.00004246017,0.005082825],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004275977,"threshold_uncertainty_score":0.01604283,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02099988518953467,"score_gpt":0.2619631762806928,"score_spread":0.2409632910911581,"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."}}