{"id":"W4249544772","doi":"10.32920/ryerson.14647299","title":"Numerical Analysis of Film Cooling Performance of Micro Holes and Compound Angle Sister Holes","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Heat Transfer Mechanisms","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Turbulence; Freestream; Reynolds-averaged Navier–Stokes equations; Coolant; Mechanics; Materials science; Reynolds stress; Computational fluid dynamics; Jet (fluid); Cooling flow; Reynolds number; Turbulence kinetic energy; Vortex; Physics; Thermodynamics","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":[0.0001853535,0.0002348425,0.0002328708,0.000208541,0.0001735231,0.000251378,0.0002492843,0.0003153632,0.00099838],"category_scores_gemma":[0.0005780578,0.0001011921,0.0002177872,0.0001663124,0.0003281713,0.0002291748,0.0001809597,0.0001218132,0.00005567635],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000195745,"about_ca_system_score_gemma":0.0002869687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002744386,"about_ca_topic_score_gemma":0.001901751,"domain_scores_codex":[0.9999342,0.00000892064,0.000002742429,0.00001192482,0.00002382256,0.00001836523],"domain_scores_gemma":[0.9998198,0.00008351495,0.00003129354,0.00001667298,0.00003699121,0.00001176655],"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":[0.0006522097,0.00006885623,0.008964189,0.0003447528,0.00002740027,0.0004167622,0.000243838,0.6788091,0.2809097,0.005639489,0.0005857369,0.02333795],"study_design_scores_gemma":[0.00002449205,0.0002789077,0.002694749,0.00001076834,0.00001045447,0.00005750796,0.00007908272,0.9691037,0.02676606,0.0001905344,0.000772346,0.00001140468],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9760563,0.0001838176,0.02078658,0.000036996,0.00002605363,0.00002703734,0.00006750866,0.00008624992,0.002729403],"genre_scores_gemma":[0.9905004,0.00005245428,0.008791585,0.000002836555,0.000001967147,0.00001359211,0.00002324109,0.000006448022,0.0006075554],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002744386,"threshold_uncertainty_score":0.005456805,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01655218274720098,"score_gpt":0.2243844204380393,"score_spread":0.2078322376908383,"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."}}