{"id":"W4393253846","doi":"10.1007/s10494-024-00539-1","title":"Exploring the Potential and the Practical Usability of a Machine Learning Approach for Improving Wall Friction Predictions of RANS Wall Functions in Non-equilibrium Turbulent Flows","year":2024,"lang":"en","type":"article","venue":"Flow Turbulence and Combustion","topic":"Fluid Dynamics and Turbulent Flows","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Reynolds-averaged Navier–Stokes equations; Usability; Turbulence; Mechanics; Computer science; Mechanical engineering; Aerospace engineering; Marine engineering; Engineering; Physics; Human–computer interaction","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":[0.000729478,0.00016569,0.0002224451,0.0001188194,0.0001424279,0.00006401721,0.00008252256,0.00007434655,0.000004096049],"category_scores_gemma":[0.00006828266,0.0001113627,0.0001028006,0.000265419,0.0001208187,0.0003915538,0.00004450199,0.0004181934,4.355798e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004698563,"about_ca_system_score_gemma":0.0000225401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002091097,"about_ca_topic_score_gemma":0.0000301316,"domain_scores_codex":[0.998906,0.00006446921,0.0003929041,0.0002600122,0.0001766162,0.0001999682],"domain_scores_gemma":[0.9994475,0.0002271347,0.00004420908,0.0001817003,0.00005924462,0.00004023724],"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":[0.0001595001,0.0000563268,0.0002367681,0.0006314649,0.00005212214,8.671954e-7,0.001200233,0.9903214,0.001555683,0.0004712831,0.00002280042,0.005291547],"study_design_scores_gemma":[0.0007107455,0.00009338344,0.001946696,0.00008548112,0.0001417271,0.00002327346,0.0001910255,0.9963709,0.00007792127,0.000180041,0.00007367678,0.0001051567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7649978,0.001099218,0.2321092,0.0005173673,0.0004455116,0.0006819668,0.0000243771,0.00008595376,0.00003867692],"genre_scores_gemma":[0.9974872,0.0005414867,0.001543752,0.000007461043,0.00008468351,0.0002341869,0.00004747215,0.00002191064,0.00003186789],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2324894,"threshold_uncertainty_score":0.4541238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01506539527873407,"score_gpt":0.2102464662366864,"score_spread":0.1951810709579523,"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."}}