{"id":"W2033900405","doi":"10.1109/mwscas.2011.6026604","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":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Artificial neural network; Computer science; Fault (geology); Perceptron; Gas turbines; Multilayer perceptron; Turbine; Artificial intelligence; Control engineering; Machine learning; 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":[0.0003683164,0.0005528916,0.0004780994,0.0007237897,0.0002420714,0.0005150769,0.0005281385,0.0006211071,0.0004251455],"category_scores_gemma":[0.001472407,0.0002472909,0.0003044194,0.0002680513,0.000309657,0.0008064278,0.0003402942,0.0003892105,0.000100668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000553637,"about_ca_system_score_gemma":0.0002903612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002823074,"about_ca_topic_score_gemma":0.002344741,"domain_scores_codex":[0.999756,0.00005824954,0.0000166736,0.0000567147,0.00009021014,0.00002206265],"domain_scores_gemma":[0.9996369,0.0001828906,0.0000706448,0.00002130506,0.00007639807,0.00001183076],"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":[0.0002112684,0.00005586877,0.00196251,0.0001464875,0.00007586175,0.0002487483,0.00006153218,0.7433249,0.02788683,0.005206022,0.0005007679,0.2203191],"study_design_scores_gemma":[0.000005094542,0.00002482835,0.0002595019,0.000005350462,0.000008587392,0.0000350179,0.000004039881,0.9949479,0.003028282,0.001373689,0.0003018126,0.000005918283],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04586278,0.001140013,0.9505324,0.0001696832,0.00005309321,0.00002681974,0.00003422878,0.0006915645,0.001489436],"genre_scores_gemma":[0.9181783,0.0004207901,0.0803377,0.00004544695,0.00003333098,0.00002968434,0.00006031271,0.00002050855,0.0008739427],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002823074,"threshold_uncertainty_score":0.005613267,"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."}}