{"id":"W2969579909","doi":"10.4050/f-0075-2019-14634","title":"Enhancement of an Engineering Simulation Model to Improve the Correlation with Flight Test Data in Climb/Descent and Autorotation","year":2019,"lang":"en","type":"article","venue":"","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Fuselage; Climb; Descent (aeronautics); Flight simulator; Rotor (electric); Flight test; Test data; Engineering; Aerodynamics; Simulation; Computer science; Aerospace engineering; Mechanical 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":[0.00006989576,0.00006257416,0.00006924196,0.0000518486,0.000009083026,0.000009031009,0.00007815331,0.00003918861,0.000007082611],"category_scores_gemma":[0.00001610663,0.00004639039,0.000003227325,0.0001036624,0.000004507768,0.0002297835,0.00002850395,0.00005597787,0.00000471975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003123573,"about_ca_system_score_gemma":0.000005695333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001030077,"about_ca_topic_score_gemma":0.0000492192,"domain_scores_codex":[0.9996008,0.000002631131,0.0001258909,0.0001180194,0.00007476936,0.0000778624],"domain_scores_gemma":[0.9996403,0.00003730265,0.00002282118,0.0002649315,0.00001913288,0.0000154796],"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":[0.000004233623,0.00001181332,0.003379713,0.00001747859,0.000002872898,4.448203e-8,0.0002403144,0.9627659,0.03120327,0.000267916,0.000003431703,0.002102996],"study_design_scores_gemma":[0.000203779,0.00008325953,0.007302588,0.0000166784,0.000003891696,1.320877e-7,0.0000755599,0.9801846,0.0120268,0.0000142886,0.00002611712,0.00006235627],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7004661,0.00001204827,0.2990251,0.00005823861,0.00002981263,0.0002812677,0.000003874855,0.00005882932,0.00006470155],"genre_scores_gemma":[0.9948338,0.000005203984,0.005038581,0.00001429304,0.000006496008,0.00001035137,0.00002712541,0.000009782927,0.0000543921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2943677,"threshold_uncertainty_score":0.1891745,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007836884266702947,"score_gpt":0.2199290915847605,"score_spread":0.2120922073180576,"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."}}