{"id":"W2043039095","doi":"10.1016/j.ins.2013.05.032","title":"Fault detection and isolation of a dual spool gas turbine engine using dynamic neural networks and multiple model approach","year":2013,"lang":"en","type":"article","venue":"Information Sciences","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":156,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"","keywords":"Jet engine; Artificial neural network; Fault detection and isolation; Computer science; Fault (geology); Noise (video); Control theory (sociology); Jet (fluid); Turbine; Isolation (microbiology); Artificial intelligence; Engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002312376,0.0007881998,0.0007980779,0.0005420142,0.0005764026,0.0005084884,0.0005614742,0.0008226317,0.0006296503],"category_scores_gemma":[0.0008739654,0.0003135931,0.0003963813,0.0001767824,0.0003389119,0.0006158621,0.0004532771,0.0005378954,0.00009359074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004797312,"about_ca_system_score_gemma":0.0005162213,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005338967,"about_ca_topic_score_gemma":0.004867456,"domain_scores_codex":[0.9998652,0.00001963836,0.000009989933,0.00004349431,0.0000345006,0.00002717068],"domain_scores_gemma":[0.9996061,0.0001853319,0.000069539,0.00002629157,0.00008368755,0.00002909762],"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":[0.002042457,0.0003509572,0.006755367,0.0002570617,0.0002118129,0.0009857585,0.0001755773,0.757214,0.09884277,0.002416107,0.0007124768,0.1300357],"study_design_scores_gemma":[0.000008977754,0.00007146739,0.0009490477,0.000002958235,0.00001592305,0.00003897286,0.00001212692,0.9922654,0.006222612,0.0003328606,0.00007272539,0.00000681508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.679614,0.0004855937,0.3160417,0.0004248784,0.0001427593,0.00004064884,0.00005169589,0.0007722498,0.002426554],"genre_scores_gemma":[0.9949706,0.00002285492,0.004547528,0.00001108894,0.000004362674,0.00000595768,0.00001376427,0.00000445567,0.0004194326],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.005338967,"threshold_uncertainty_score":0.01061577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01039580755824796,"score_gpt":0.2073026387603611,"score_spread":0.1969068312021131,"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."}}