{"id":"W2123865867","doi":"10.1016/j.jprocont.2004.06.008","title":"An optimal scheme for fast rate fault detection based on multirate sampled data","year":2004,"lang":"en","type":"article","venue":"Journal of Process Control","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":48,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Residual; Fault detection and isolation; Control theory (sociology); Computer science; Generator (circuit theory); Constraint (computer-aided design); Key (lock); Fault (geology); LTI system theory; Invariant (physics); Algorithm; Mathematics; Power (physics); Linear system; Control (management); Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006101784,0.0001935498,0.0003578157,0.0001856173,0.00009765912,0.0001152164,0.0003745811,0.0001058012,0.00001121078],"category_scores_gemma":[0.0001845728,0.0001644735,0.0001039684,0.0001419609,0.00001486103,0.0005741975,0.000004035213,0.0002594884,0.00000711143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001062643,"about_ca_system_score_gemma":0.00008407424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006142388,"about_ca_topic_score_gemma":0.00003226071,"domain_scores_codex":[0.9987417,0.00004580161,0.0005346071,0.0001842528,0.0002412951,0.0002523705],"domain_scores_gemma":[0.9989085,0.00008396055,0.0002458829,0.0003025264,0.0003030759,0.0001560666],"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":[0.001221693,0.00007800518,0.00001680452,0.00008972325,0.00009156376,0.000007376109,0.00006536361,0.8990088,0.08760149,0.000004606813,0.00002028975,0.01179427],"study_design_scores_gemma":[0.01194245,0.000688697,0.0001050716,0.00007788275,0.00005510491,0.00002539212,0.0001072154,0.9675152,0.01728555,0.0000217352,0.001994671,0.0001809775],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.176598,0.0001114367,0.82173,0.0001792778,0.000706701,0.0004330124,0.00007717291,0.0001228143,0.00004166387],"genre_scores_gemma":[0.9976081,0.000004938317,0.00152913,0.0001976296,0.0005632484,0.00003938852,0.000008356423,0.00004279246,0.000006378645],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8210102,"threshold_uncertainty_score":0.6707033,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01800453897499,"score_gpt":0.2772723422210838,"score_spread":0.2592678032460938,"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."}}