{"id":"W2046805638","doi":"10.1109/icqr.2011.6031675","title":"Fault diagnosis of gas turbine engines by using dynamic neural networks","year":2011,"lang":"en","type":"article","venue":"","topic":"Fault Detection and Control Systems","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Artificial neural network; Computer science; Fault (geology); Perceptron; Multilayer perceptron; Gas turbines; Network architecture; Control engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004470441,0.0001196358,0.0001741665,0.00005120388,0.00001952462,0.000009106475,0.0000810503,0.00007125892,0.0001733094],"category_scores_gemma":[0.000006652372,0.0001059682,0.00006370062,0.0001306707,0.00001366289,0.00007745645,0.000009721441,0.00008239966,0.000005270523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002346882,"about_ca_system_score_gemma":0.000001533602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000357453,"about_ca_topic_score_gemma":0.00006816205,"domain_scores_codex":[0.9994301,0.00001380701,0.0002155787,0.00009347102,0.0000724056,0.0001746252],"domain_scores_gemma":[0.9997441,0.00002176634,0.00002592846,0.0001341315,0.00002265919,0.00005145432],"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":[0.00004162594,0.0001025823,0.01028253,0.0001753893,0.0002812596,0.00001088347,0.0005007413,0.8935418,0.03613111,0.00007900734,0.004863777,0.05398936],"study_design_scores_gemma":[0.0002249559,0.0000246295,0.000277631,0.00001260547,0.00001424404,0.000007146699,0.00004811666,0.9954364,0.003359553,0.000003837904,0.0004730455,0.0001178431],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9639813,0.001304375,0.03117041,0.00001127896,0.0008978167,0.0001455606,0.000006119957,0.0003771539,0.002106033],"genre_scores_gemma":[0.9995617,0.00004798113,0.0001390464,0.00001912749,0.00004224061,0.00001845154,0.000002760361,0.00002563337,0.0001430875],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1018947,"threshold_uncertainty_score":0.4321258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01041379782288878,"score_gpt":0.2044906393671147,"score_spread":0.1940768415442259,"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."}}