{"id":"W1979445498","doi":"10.2514/1.27577","title":"Trailing-Edge Flap Control of Dynamic Pitching Moment","year":2007,"lang":"en","type":"article","venue":"AIAA Journal","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Pitching moment; Trailing edge; Lift coefficient; Mechanics; Deflection (physics); Leading edge; Angle of attack; Wing; Stall (fluid mechanics); Aerodynamics; Lift (data mining); Materials science; Physics; Structural engineering; Engineering; Reynolds number; Optics; Computer science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001430634,0.0002394287,0.0001732561,0.0001199613,0.0001299967,0.000187455,0.0001740122,0.00009591638,0.0008271206],"category_scores_gemma":[0.0004884618,0.0000813474,0.0001069289,0.00005620957,0.0001468666,0.0001567084,0.0001952557,0.0001800112,0.0001068522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005858439,"about_ca_system_score_gemma":0.00007542954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001422226,"about_ca_topic_score_gemma":0.000228179,"domain_scores_codex":[0.999954,0.000006003403,0.000002832936,0.0000100406,0.00001342682,0.00001357951],"domain_scores_gemma":[0.9997434,0.0001366908,0.00004127159,0.00002752513,0.00002944242,0.00002169263],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006362041,0.00006445902,0.000929963,0.0001095347,0.000008608677,0.0001893035,0.00006168398,0.01597955,0.9329047,0.0007072205,0.00008394927,0.04832481],"study_design_scores_gemma":[0.0001605573,0.001322834,0.005332442,0.00001731631,0.00003265465,0.0002412415,0.0000344006,0.2438059,0.7468156,0.0006063209,0.001602728,0.00002801156],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9749787,0.0002164932,0.02247916,0.00001948373,0.00002401344,0.00001801004,0.0000221287,0.000154843,0.002087018],"genre_scores_gemma":[0.997505,0.00004343586,0.002197632,0.000002455806,0.000003170423,0.00000397038,0.000005146871,0.000004740145,0.0002345343],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008271206,"threshold_uncertainty_score":0.002767026,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003075725721725507,"score_gpt":0.2103441987456371,"score_spread":0.2072684730239116,"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."}}