{"id":"W2956475623","doi":"10.29252/jafm.12.06.29895","title":"Numerical Investigation on the Effects of Internal Flow Structure on Ejector Performance","year":2019,"lang":"en","type":"article","venue":"Journal of Applied Fluid Mechanics","topic":"Refrigeration and Air Conditioning Technologies","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Injector; Nozzle; Mechanics; Computational fluid dynamics; Flow (mathematics); Internal flow; Refrigeration; Range (aeronautics); Work (physics); Materials science; Computer simulation; Flow conditions; Mechanical engineering; Physics; Engineering","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":[0.0004734297,0.0003325824,0.0005217487,0.0003155915,0.0003208423,0.000506947,0.0003591935,0.0005152119,0.001571619],"category_scores_gemma":[0.001874503,0.0001564939,0.0003313737,0.0003155359,0.0004347791,0.0003370132,0.0003472233,0.0003166343,0.0001531296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003158757,"about_ca_system_score_gemma":0.0003236382,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001236597,"about_ca_topic_score_gemma":0.001112751,"domain_scores_codex":[0.9998438,0.00002698248,0.00000989011,0.00002698794,0.00006018433,0.0000321316],"domain_scores_gemma":[0.999023,0.0006388446,0.00007734507,0.00007956841,0.0001565947,0.00002471995],"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":[0.0005944754,0.0002256531,0.01039312,0.0004513381,0.000032463,0.0002707099,0.0002704792,0.8095495,0.1478595,0.002606441,0.0004589796,0.02728738],"study_design_scores_gemma":[0.00003121662,0.000342352,0.004031479,0.00001668141,0.00001878696,0.00008572998,0.00005794842,0.9230896,0.07146318,0.0001876169,0.0006545749,0.00002084924],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9648171,0.000200746,0.02991486,0.00006668219,0.00002145976,0.00004000037,0.0002269034,0.000222569,0.004489593],"genre_scores_gemma":[0.9900594,0.0001167002,0.00882285,0.000008342052,0.000003131762,0.00001634334,0.0001123965,0.00002476505,0.0008359216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001571619,"threshold_uncertainty_score":0.005257607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004864893986344984,"score_gpt":0.1716260546231379,"score_spread":0.1667611606367929,"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."}}