{"id":"W2909897635","doi":"10.2514/6.2019-1627","title":"Computational Simulation of 3-D Riblets for Skin Friction Drag Reduction","year":2019,"lang":"en","type":"article","venue":"AIAA Scitech 2019 Forum","topic":"Rheology and Fluid Dynamics Studies","field":"Chemical Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lockheed Martin (Canada)","funders":"Air Force Research Laboratory","keywords":"Drag; Reduction (mathematics); Parasitic drag; Computer science; Materials science; Mechanics; Physics; Mathematics; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001132374,0.00009782449,0.0001611926,0.000109536,0.00007324035,0.000005583335,0.00007607212,0.0001257911,0.00003544777],"category_scores_gemma":[0.00004707498,0.00009905894,0.00008269041,0.0001496926,0.00003580585,0.0001532966,0.0000354685,0.00008649095,0.00005613224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004414321,"about_ca_system_score_gemma":0.00001049838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001202411,"about_ca_topic_score_gemma":0.000001353511,"domain_scores_codex":[0.9992681,0.00000849606,0.0002297352,0.0001844797,0.000122316,0.0001869056],"domain_scores_gemma":[0.9994625,0.0001553959,0.00009024959,0.0001282369,0.0001424398,0.00002122003],"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":[0.00005616594,0.00003099111,0.001431118,0.00004132278,0.00004715077,5.211759e-8,0.0000924788,0.9177955,0.04683836,0.03196057,0.000828601,0.0008777079],"study_design_scores_gemma":[0.0005196683,0.0000789843,0.001061488,0.00002091508,0.00001379722,0.000002050084,0.00006222224,0.9878431,0.004408605,0.00539869,0.0004824543,0.0001080506],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2584774,0.00008522812,0.7395267,0.0003104127,0.0005739331,0.000323665,0.00002796065,0.00007741251,0.0005973076],"genre_scores_gemma":[0.9914402,0.000006233742,0.005813213,0.00002540982,0.00005847173,0.00001636042,0.000105065,0.00001497277,0.002520041],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7337134,"threshold_uncertainty_score":0.4039506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006321541179762225,"score_gpt":0.2421783797033875,"score_spread":0.2358568385236253,"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."}}