{"id":"W2620920098","doi":"10.2514/6.2017-3152","title":"Methodology of Estimation of Aerodynamic Coefficients of the UAS-E4 Ehécatl using Datcom and VLM Procedure","year":2017,"lang":"en","type":"article","venue":"AIAA Modeling and Simulation Technologies Conference","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Aerodynamics; Estimation; Computer science; Aerospace engineering; Engineering; Systems engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003513783,0.0004163623,0.0003346526,0.0007899894,0.0004287476,0.0005409775,0.0006041722,0.0004408566,0.002963905],"category_scores_gemma":[0.0007462725,0.0001998754,0.0003872193,0.0004044239,0.0001756236,0.0003319099,0.000543787,0.0004739372,0.0008036711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002514724,"about_ca_system_score_gemma":0.0007732895,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004414005,"about_ca_topic_score_gemma":0.002921495,"domain_scores_codex":[0.9998046,0.0000474099,0.000009822028,0.00004972806,0.00006587017,0.00002267466],"domain_scores_gemma":[0.9997912,0.00005369756,0.00002527687,0.00002255664,0.00009851969,0.000008763514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002141206,0.0001325518,0.009472679,0.0003920552,0.00009196179,0.0002962124,0.0001996452,0.3951178,0.1038595,0.01684928,0.002568008,0.4708063],"study_design_scores_gemma":[0.00001725641,0.00008074488,0.003782666,0.00001979127,0.00001904728,0.00009830555,0.00007019172,0.9592682,0.03113078,0.001640511,0.003847098,0.00002543243],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0188895,0.0000659841,0.9780589,0.00002086833,0.00001758305,0.0000573754,0.0001099327,0.0004776182,0.002302211],"genre_scores_gemma":[0.4577779,0.0001656048,0.536011,0.00002983683,0.00002547705,0.0002953715,0.0006143198,0.0001095032,0.004970918],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004414005,"threshold_uncertainty_score":0.009915233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06399476858947185,"score_gpt":0.3080852002315478,"score_spread":0.244090431642076,"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."}}