{"id":"W2949278708","doi":"10.82308/6025","title":"Modeling and control of a flying wing tailsitter unmanned aerial vehicle","year":2018,"lang":"en","type":"article","venue":"eScholarship@McGill (McGill)","topic":"Aerospace Engineering and Control Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada","keywords":"Climb; Takeoff; Takeoff and landing; Fly-by-wire; Flight control surfaces; Aerospace engineering; Descent (aeronautics); Flight simulator; Thrust; Aircraft flight mechanics; Flight test; Aileron; Airplane; Aerodynamics; Fixed wing; Engineering; Wing; Lift (data mining); Aeronautics; Wing loading; Angle of attack; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001319568,0.0005726151,0.0002949324,0.0001974742,0.0003244232,0.0006355885,0.0006024385,0.0005945587,0.001945912],"category_scores_gemma":[0.0001850243,0.0001888297,0.0003322838,0.0001295727,0.0003711508,0.0003412723,0.0003716259,0.0003865059,0.0003245738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000388684,"about_ca_system_score_gemma":0.0006871979,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02150142,"about_ca_topic_score_gemma":0.009260096,"domain_scores_codex":[0.9999162,0.00001405027,0.000003185725,0.00001663849,0.00003636954,0.00001354982],"domain_scores_gemma":[0.9999416,0.00001622083,0.00001444859,0.000005377285,0.00001582043,0.000006578399],"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":[0.00002667305,0.0000138766,0.0004008316,0.00002107096,0.000007529696,0.00008895699,0.00004085371,0.986707,0.005800993,0.002020975,0.0002021938,0.004668992],"study_design_scores_gemma":[0.000004785677,0.00003826543,0.0002072472,0.000002008544,0.000002515288,0.00001004615,0.000007316866,0.9986243,0.0004055509,0.0001955673,0.0005000001,0.000002386551],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2243275,0.0003593529,0.7469069,0.0002143542,0.00007639326,0.0001727303,0.000409971,0.001086598,0.02644621],"genre_scores_gemma":[0.9753923,0.0002267584,0.01523628,0.00002972767,0.00001406255,0.0001208245,0.0001970942,0.00003010222,0.0087528],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02150142,"threshold_uncertainty_score":0.04275256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008759878609154184,"score_gpt":0.1864221231969591,"score_spread":0.1776622445878049,"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."}}