{"id":"W4391606965","doi":"10.1002/cjce.25204","title":"Estimation of turbulent energy mixing factor in <scp>PWR</scp> sub‐channel by <scp>DNS</scp>","year":2024,"lang":"en","type":"article","venue":"The Canadian Journal of Chemical Engineering","topic":"Nuclear Engineering Thermal-Hydraulics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Turbulence; Mixing (physics); Reynolds number; Context (archaeology); Direct numerical simulation; Mechanics; Thermal hydraulics; Physics; Channel (broadcasting); Pressurized water reactor; Heat transfer; Computer science; Nuclear physics; Geology; Telecommunications","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002690524,0.0003090666,0.0003821009,0.0004482369,0.00002504319,0.0001018966,0.0004516317,0.0002038769,0.000005163608],"category_scores_gemma":[0.0004062141,0.0002910221,0.0001586739,0.0004905636,0.00004176824,0.0002381665,0.00002226483,0.0007536035,0.000007320787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005592068,"about_ca_system_score_gemma":0.0001339592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002444584,"about_ca_topic_score_gemma":0.0000737446,"domain_scores_codex":[0.9983581,0.00001555118,0.0006016807,0.0001485313,0.0002868471,0.0005893264],"domain_scores_gemma":[0.9987771,0.0004363457,0.00006922593,0.0002167184,0.00004636659,0.0004542557],"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":[4.231793e-7,0.000004911416,0.00000346999,0.0001850988,0.00008563345,0.00007136586,0.0007943419,0.798781,0.1961977,0.0002061294,0.002569389,0.001100461],"study_design_scores_gemma":[0.0001475369,0.00001698079,0.00003616028,0.0003937615,0.00002504397,0.0001396594,0.00002715074,0.6715951,0.3213494,0.0001032149,0.006096312,0.00006973656],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795665,0.006232268,0.01281843,0.0001108401,0.0007965891,0.00008238374,0.00002758523,0.0001506184,0.0002147784],"genre_scores_gemma":[0.9991032,0.00004488731,0.0004192452,0.00002416248,0.0002210277,0.000004620726,0.000007501478,0.0001426232,0.00003271416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1271859,"threshold_uncertainty_score":0.9999542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005385703984261189,"score_gpt":0.1717996319245668,"score_spread":0.1664139279403056,"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."}}