{"id":"W4252401294","doi":"10.32920/14669073.v1","title":"Effects of wake shapes on high-lift system aerodynamic predictions","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Aerodynamics and Fluid Dynamics Research","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Kenneth M. Molson Foundation; Molson Foundation","keywords":"Wake; Freestream; Lift (data mining); Aerodynamics; Trailing edge; Mechanics; Lift-to-drag ratio; Drag; Leading edge; Lift coefficient; Aerospace engineering; Physics; Computer science; Engineering; Reynolds number","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000203108,0.0004573838,0.0007172992,0.0003410663,0.00006900277,0.0001113634,0.0005273729,0.0005630136,0.00006818989],"category_scores_gemma":[0.00004326506,0.0004498658,0.0002881547,0.0002579717,0.0000717598,0.00004982979,0.0005443051,0.001110379,0.00003380034],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004909714,"about_ca_system_score_gemma":0.0001113833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002947709,"about_ca_topic_score_gemma":0.0005099226,"domain_scores_codex":[0.997748,0.00008201527,0.0005575052,0.0005614107,0.0005947612,0.0004563202],"domain_scores_gemma":[0.9986517,0.0002364062,0.00007146524,0.0006867414,0.000188201,0.0001655262],"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":[0.000009627788,0.000113648,0.00006071709,0.008363872,0.0005526222,0.00006924386,0.00009080333,0.9547426,0.01655634,0.01850962,0.0002709778,0.0006599039],"study_design_scores_gemma":[0.0002795801,0.00005633952,0.01310319,0.001082035,0.00007999216,0.000004941778,0.00007240356,0.9843532,0.0005381522,0.00005442022,0.0000183244,0.0003574561],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8917128,0.0007898745,0.08804365,0.00004000951,0.002387662,0.001032472,0.0002847805,0.001039304,0.0146694],"genre_scores_gemma":[0.9966265,0.0006092882,0.001244038,0.000007024522,0.0001344923,0.0001930137,0.0003087379,0.0001319052,0.0007450231],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1049136,"threshold_uncertainty_score":0.9997953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005014108693339167,"score_gpt":0.2092511142514664,"score_spread":0.2042370055581272,"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."}}