{"id":"W2032837898","doi":"10.1016/j.jprocont.2013.08.002","title":"A unified framework for fault detection and isolation of sensor and actuator biases in linear time invariant systems using marginalized likelihood ratio test with uniform priors","year":2013,"lang":"en","type":"article","venue":"Journal of Process Control","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Prior probability; Fault detection and isolation; Benchmark (surveying); Fault (geology); Realization (probability); Likelihood-ratio test; Invariant (physics); Statistical hypothesis testing; Mathematics; Actuator; Control theory (sociology); Computer science; Algorithm; Statistics; Artificial intelligence; Bayesian probability","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":[0.0003193965,0.0001459834,0.0004316859,0.0002339534,0.00004579114,0.00008200244,0.00004627175,0.0001238029,0.000003715552],"category_scores_gemma":[0.0003987306,0.0001111923,0.00003417037,0.0001820372,0.00002133135,0.0003967553,0.000002942576,0.0001721098,5.590534e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006010648,"about_ca_system_score_gemma":0.00005777081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005642161,"about_ca_topic_score_gemma":0.00002459765,"domain_scores_codex":[0.9989769,0.00004007597,0.000561548,0.00009554923,0.0001599723,0.0001659211],"domain_scores_gemma":[0.9987133,0.0003888739,0.0003900516,0.00006468147,0.0003538852,0.00008917838],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001986875,0.0001281052,0.004258473,0.001870438,0.0004578509,0.00001217826,0.001850738,0.214683,0.7702051,0.00004415984,0.000007312458,0.004495783],"study_design_scores_gemma":[0.004242585,0.0004591461,0.0007573852,0.0006137502,0.00008292771,0.0001482346,0.0008179801,0.9902418,0.002425513,0.00006522475,0.00001728624,0.0001282307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7837616,0.0003295447,0.2150118,0.00003904016,0.00009814936,0.0007261041,0.000007642384,0.00002069721,0.000005415356],"genre_scores_gemma":[0.997552,0.00001923933,0.002225131,0.0000119418,0.0001225201,0.00003674817,4.4227e-7,0.00002401668,0.000007921079],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7755587,"threshold_uncertainty_score":0.4534289,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01019086828640053,"score_gpt":0.2314263555335034,"score_spread":0.2212354872471029,"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."}}