{"id":"W2922715720","doi":"10.1109/tns.2019.2906604","title":"Fault Detection and Identification for Sensor Channels in Steam Generator Level Control Loops","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Nuclear Science","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Redundancy (engineering); Fault detection and isolation; Transient (computer programming); Engineering; Process (computing); Control system; Boiler (water heating); Fault (geology); Computer science; Control engineering; Reliability engineering; Control theory (sociology); Control (management); Actuator; Electrical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003923276,0.0003048062,0.0003261729,0.0003852184,0.0002183911,0.0002995272,0.0003058503,0.0004456687,0.0005470106],"category_scores_gemma":[0.002032198,0.0001030286,0.0002061096,0.0001806079,0.0003821534,0.0004524444,0.0002273787,0.000276352,0.00006339287],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003057661,"about_ca_system_score_gemma":0.0003285902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007327537,"about_ca_topic_score_gemma":0.0007211249,"domain_scores_codex":[0.9996734,0.0000949158,0.00001486618,0.00004328504,0.0001361248,0.00003739758],"domain_scores_gemma":[0.9991298,0.0005176984,0.0001730462,0.00005784979,0.0001091,0.00001245345],"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":[0.0005612395,0.00009151217,0.004460151,0.0002960711,0.00004025197,0.0004766482,0.0003526108,0.693878,0.1008938,0.01692665,0.0006771349,0.1813459],"study_design_scores_gemma":[0.000009085367,0.00009805508,0.000539251,0.000006720419,0.00000658358,0.0001250412,0.00001876094,0.9773982,0.01979692,0.001712585,0.0002822787,0.000006530784],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1227432,0.0001559563,0.8757747,0.00006660495,0.0000128377,0.000036008,0.0000170228,0.000392265,0.0008014623],"genre_scores_gemma":[0.9750319,0.00003767512,0.02469204,0.000009111548,0.000004322266,0.00001122104,0.00001042386,0.000004969227,0.0001982569],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0007327537,"threshold_uncertainty_score":0.002218544,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01236988044608982,"score_gpt":0.2180135178938755,"score_spread":0.2056436374477856,"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."}}