{"id":"W2334994701","doi":"10.14510/39ara2015.3916","title":"Optimization of Engine Model Parameters Gain and Time Constant for the Cessna Citation X Business Aircraft Engine","year":2015,"lang":"en","type":"article","venue":"","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure; Université du Québec à Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Constant (computer programming); Turboprop; Aerospace engineering; Aero engine; Automotive engineering; Computer science; Mechanical engineering; Engineering; Physics; Materials science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0004235566,0.001012587,0.0005206148,0.0006161786,0.000436145,0.000745648,0.0004658248,0.000724823,0.002962308],"category_scores_gemma":[0.001291141,0.0002889236,0.0006233366,0.0003066407,0.0001930734,0.0005063807,0.0003854164,0.0007156834,0.0007304452],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004559044,"about_ca_system_score_gemma":0.0008005991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007163359,"about_ca_topic_score_gemma":0.005610816,"domain_scores_codex":[0.9998412,0.00002574768,0.000009159264,0.00003148751,0.0000585315,0.00003377968],"domain_scores_gemma":[0.9996227,0.0001564148,0.00004269158,0.00004009061,0.0001161673,0.00002197658],"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":[0.0003924338,0.0001901751,0.002558603,0.0003888803,0.00005118582,0.0001346068,0.0001004858,0.9321156,0.03399554,0.001051547,0.001226126,0.02779485],"study_design_scores_gemma":[0.0001137837,0.0006171057,0.004851136,0.00003627793,0.0001062024,0.00007585511,0.0001224477,0.9513276,0.037553,0.000424635,0.004727366,0.00004463249],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7740683,0.001090497,0.1877253,0.0003102611,0.0001148555,0.0003310244,0.001291831,0.001811014,0.03325696],"genre_scores_gemma":[0.9848413,0.0001391817,0.01238858,0.00001602608,0.000002971876,0.00008623771,0.000462486,0.0001185498,0.001944599],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007163359,"threshold_uncertainty_score":0.0142433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01786901593891847,"score_gpt":0.2090461478432055,"score_spread":0.1911771319042871,"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."}}