{"id":"W2139006349","doi":"10.1109/tcst.2006.883193","title":"Hybrid System State Tracking and Fault Detection Using Particle Filters","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Control Systems Technology","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Space Agency","funders":"","keywords":"Tracking (education); Particle filter; Fault detection and isolation; Fault (geology); State (computer science); Computer science; Mode (computer interface); Hybrid system; Algorithm; Control theory (sociology); Particle (ecology); Artificial intelligence; Kalman filter; Machine learning","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":[0.00122735,0.0005751043,0.0008725409,0.0006784416,0.0003716807,0.00103002,0.000727988,0.001287615,0.0009459133],"category_scores_gemma":[0.003228715,0.0004003896,0.0005550992,0.0006403261,0.0007676449,0.00120895,0.0007151111,0.0008748965,0.0002183338],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007661278,"about_ca_system_score_gemma":0.0008101024,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006305174,"about_ca_topic_score_gemma":0.003560451,"domain_scores_codex":[0.9994442,0.0001473916,0.00003369923,0.0001517192,0.000178462,0.00004450513],"domain_scores_gemma":[0.998462,0.00101318,0.0001709059,0.0001264019,0.0001951946,0.00003239967],"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":[0.000160239,0.00006263804,0.001444877,0.00007613294,0.00010703,0.0000866117,0.0001053435,0.839452,0.006766786,0.01866438,0.0007197622,0.1323542],"study_design_scores_gemma":[0.000007677967,0.00001156896,0.0001355106,0.000001986629,0.00000453067,0.00001170864,0.000002479564,0.9966156,0.001122482,0.001752694,0.0003286813,0.000004990605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005720725,0.00005605081,0.9936244,0.00003523374,0.00001914093,0.00001150254,0.000007013367,0.0001781118,0.0003478159],"genre_scores_gemma":[0.5277532,0.0002115634,0.4684582,0.00008063968,0.00006739028,0.0001496341,0.00007278215,0.00004742,0.003159164],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006305174,"threshold_uncertainty_score":0.012537,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00630178836320826,"score_gpt":0.1930096655207919,"score_spread":0.1867078771575836,"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."}}