{"id":"W4392094147","doi":"10.1016/j.ijrefrig.2024.02.020","title":"A homogeneous relaxation model algorithm in density-based formulation with novel tabulated method for the modeling of CO2 flashing nozzles","year":2024,"lang":"en","type":"article","venue":"International Journal of Refrigeration","topic":"Refrigeration and Air Conditioning Technologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Natural Resources Canada; Hydro-Québec","keywords":"Flashing; Nozzle; Metastability; Solver; Flow (mathematics); Relaxation (psychology); Mechanics; Homogeneous; Statistical physics; Algorithm; Computational fluid dynamics; Computer science; Thermodynamics; Materials science; Applied mathematics; Physics; Mathematics; Mathematical optimization","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005059454,0.0006348317,0.0008410127,0.0003893937,0.0005835256,0.0007691009,0.001851412,0.001152531,0.005056754],"category_scores_gemma":[0.0008964972,0.000485268,0.0008885747,0.0006024606,0.0004236501,0.0009431491,0.0007903599,0.001144133,0.0007638704],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006385104,"about_ca_system_score_gemma":0.001554932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0133087,"about_ca_topic_score_gemma":0.009081115,"domain_scores_codex":[0.9998457,0.0000417255,0.000007475314,0.00002456769,0.0000549246,0.00002544266],"domain_scores_gemma":[0.9996984,0.0001330571,0.00002517733,0.000020427,0.0001027252,0.00002030361],"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":[0.00002483669,0.00005169534,0.0002771472,0.00009021736,0.00001775765,0.00006491639,0.00004832636,0.9597428,0.001957328,0.02286541,0.001451228,0.01340832],"study_design_scores_gemma":[0.000003499544,0.000005616221,0.00002214902,0.000004076512,0.000002330239,0.000005979936,0.000005649112,0.998262,0.0001770875,0.0007396951,0.0007696843,0.000002252958],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007244654,0.0003799007,0.9817436,0.000122032,0.0000838942,0.00007118745,0.0001253632,0.0002335369,0.009995888],"genre_scores_gemma":[0.4491291,0.001144323,0.5286987,0.0003085418,0.0001375645,0.000654626,0.0006223153,0.0006739603,0.01863085],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0133087,"threshold_uncertainty_score":0.0264625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01775259294820663,"score_gpt":0.2767034212060261,"score_spread":0.2589508282578195,"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."}}