{"id":"W4360617150","doi":"10.21203/rs.3.rs-2643269/v1","title":"Helicopter Performance Enhancement by Improving Retreating Blade Stall Using Active Flow Control","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Aerospace and Aviation Technology","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bell Helicopter Textron (Canada)","funders":"Cairo University","keywords":"Stall (fluid mechanics); Airfoil; Aerodynamics; Helicopter rotor; Engineering; Angle of attack; Control theory (sociology); Flow separation; Aerospace engineering; Structural engineering; Simulation; Computer science; Marine engineering; Rotor (electric); Mechanical engineering; Artificial intelligence; Control (management)","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":[0.00007872302,0.0002843132,0.0001908479,0.0001784628,0.0001613852,0.0004084294,0.0001969286,0.0002555455,0.001554442],"category_scores_gemma":[0.0001601309,0.00008407458,0.0002366982,0.00007677973,0.000165198,0.000211287,0.000171039,0.0001432433,0.0001354522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001302728,"about_ca_system_score_gemma":0.000127857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001553169,"about_ca_topic_score_gemma":0.001057746,"domain_scores_codex":[0.9999574,0.00000706528,0.000001984622,0.000007386788,0.00001687305,0.000009147303],"domain_scores_gemma":[0.999918,0.00002629842,0.00001913258,0.000008559256,0.00002144418,0.000006474152],"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":[0.0003055154,0.0002815415,0.002907204,0.0002482406,0.00003455592,0.0002534731,0.00008743001,0.6610405,0.2959208,0.001150577,0.0007896294,0.03698041],"study_design_scores_gemma":[0.00002437897,0.0007632143,0.002119796,0.0000162061,0.00002287494,0.00004128526,0.00003302383,0.949751,0.04532262,0.0002645526,0.001625708,0.00001534498],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9042896,0.0005068946,0.08456554,0.0001100642,0.0000629987,0.00005178876,0.0001155218,0.0006096411,0.009688005],"genre_scores_gemma":[0.9976485,0.0000542321,0.0017456,0.000005202899,0.000002566436,0.000005663431,0.00001933255,0.000004700185,0.0005141656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001554442,"threshold_uncertainty_score":0.005200088,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04149041988537551,"score_gpt":0.3294255845007854,"score_spread":0.2879351646154099,"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."}}