{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003152582,0.0001085899,0.0001314262,0.000271767,0.000170932,0.0001168079,0.0001066826,0.00006845673,0.00001566652],"category_scores_gemma":[0.000006572785,0.0001130193,0.00004097657,0.0003764395,0.00005714366,0.0003361992,4.31708e-7,0.0001220204,0.00009887085],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001188657,"about_ca_system_score_gemma":0.00001395711,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002794432,"about_ca_topic_score_gemma":0.00005313277,"domain_scores_codex":[0.9991032,0.00001909901,0.000205867,0.0002727009,0.0001813642,0.0002177737],"domain_scores_gemma":[0.9996269,0.00003531388,0.00002876231,0.0001782186,0.0000585618,0.0000722699],"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":[0.00003461922,0.00001844584,0.000003385595,0.00002513708,0.000006910566,2.195947e-7,0.0001805875,0.3043129,0.6747296,0.000009674757,0.000005830755,0.02067269],"study_design_scores_gemma":[0.0009726539,0.00008281242,0.0003312238,0.0000148672,0.000006722027,0.000008849089,0.0002644635,0.9448025,0.05269567,0.000004278812,0.0006824195,0.0001335677],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8231969,0.00001485635,0.174079,0.00004234273,0.001892889,0.0005534154,0.00002301937,0.0001510728,0.00004651411],"genre_scores_gemma":[0.9994572,0.00001071476,0.00009702227,0.00005049759,0.00003629339,0.0000633949,6.547002e-8,0.00002252706,0.0002623058],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6404896,"threshold_uncertainty_score":0.4608792,"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."}}