{"id":"W2912457211","doi":"10.1016/j.asej.2018.10.007","title":"Explicit solutions for turbulent flow friction factor: A review, assessment and approaches classification","year":2019,"lang":"en","type":"article","venue":"Ain Shams Engineering Journal","topic":"Water Systems and Optimization","field":"Engineering","cited_by":83,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Computation; Turbulence; Flow (mathematics); Range (aeronautics); Diagram; Mathematics; Simplicity; Applied mathematics; Mathematical optimization; Computer science; Algorithm; Engineering; Mechanics; Statistics; Geometry; Physics","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":[0.0003081225,0.0001435115,0.0001776292,0.00009736429,0.00008275159,0.0000894305,0.00006846425,0.00006713411,0.00002204162],"category_scores_gemma":[0.00001057805,0.0001329973,0.00006509624,0.00009067143,0.000002707172,0.0002577255,0.0000117336,0.0001764137,0.000007489733],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001715616,"about_ca_system_score_gemma":0.00001266989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.601418e-7,"about_ca_topic_score_gemma":4.041846e-7,"domain_scores_codex":[0.9991992,0.00001303472,0.0002896983,0.0001284187,0.0001295755,0.000240112],"domain_scores_gemma":[0.9996629,0.0000280996,0.00005206976,0.0001312893,0.00004564822,0.00007993319],"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":[0.000001339924,0.00001248152,0.0001300362,0.0007563119,0.00005512204,5.893174e-7,0.000155345,0.9899188,0.001797019,0.0004801629,0.002869904,0.003822931],"study_design_scores_gemma":[0.0001962512,0.00002694609,0.003045228,0.0004404991,0.00002091811,0.0000807738,0.0000323093,0.98685,0.00004924481,0.000009338749,0.009092797,0.0001556625],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009809824,0.004049459,0.9841778,0.0002165169,0.0007319372,0.0005408103,0.000009446104,0.0001610629,0.0003031543],"genre_scores_gemma":[0.9781872,0.002309758,0.01882625,0.00002084168,0.000304706,0.0001127237,0.00003686232,0.00005032422,0.0001513585],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9683774,"threshold_uncertainty_score":0.5423474,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04796142044760527,"score_gpt":0.2314943789454312,"score_spread":0.1835329584978259,"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."}}