{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002144436,0.0003141658,0.0004817214,0.000458767,0.0002928289,0.0001217448,0.0001217437,0.000225866,0.000002839573],"category_scores_gemma":[0.00000331147,0.0003262808,0.0001020757,0.0002947754,0.0000791795,0.000194424,8.156761e-7,0.0003623532,0.00003561375],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003419482,"about_ca_system_score_gemma":0.00001232275,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005585061,"about_ca_topic_score_gemma":0.0002864657,"domain_scores_codex":[0.9982314,0.00008802579,0.0006195357,0.0003668132,0.0002027296,0.0004914616],"domain_scores_gemma":[0.9993285,0.00006921766,0.0001044609,0.0003377255,0.00007715261,0.00008296916],"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":[0.00005324572,0.00002901236,0.00003879916,0.0001590846,0.0001330362,0.00002865733,0.00002418085,0.6870851,0.2978299,0.00008379237,0.000008321364,0.01452688],"study_design_scores_gemma":[0.001798777,0.0001031382,0.00002814135,0.0001091815,0.0000733411,0.0005587684,0.0002874612,0.8899606,0.1062374,0.00001952846,0.0005269665,0.000296687],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4800337,0.0003809889,0.5160178,0.00002221505,0.001334241,0.0004598369,0.00003382445,0.001650621,0.00006675479],"genre_scores_gemma":[0.9994233,0.000009300207,0.00003046928,0.00000909917,0.00009445586,0.00026862,5.151862e-7,0.00006975336,0.0000944506],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5193896,"threshold_uncertainty_score":0.9999189,"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."}}