{"id":"W4416702272","doi":"10.1016/j.compfluid.2025.106928","title":"Tackling compressible turbulent multi-component flows with dynamic hp-adaptation","year":2025,"lang":"en","type":"article","venue":"Computers & Fluids","topic":"Fluid Dynamics and Turbulent Flows","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"European Commission; Deutsche Forschungsgemeinschaft; European High Performance Computing Joint Undertaking","keywords":"Turbulence; Compressibility; Compressible flow; Computational fluid dynamics; Incompressible flow; Flow (mathematics)","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":[0.0002866154,0.000547561,0.0003787763,0.0002305357,0.0002647397,0.0005930705,0.0008655867,0.0007151493,0.001441622],"category_scores_gemma":[0.0007809935,0.0002220034,0.0003811812,0.000154774,0.0006834942,0.0005128691,0.001044109,0.0008194736,0.0002446213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002625223,"about_ca_system_score_gemma":0.0004802974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002670342,"about_ca_topic_score_gemma":0.001837115,"domain_scores_codex":[0.999908,0.00002524727,0.000004311019,0.0000149554,0.00003651608,0.00001109068],"domain_scores_gemma":[0.9998044,0.0001041406,0.00002151147,0.00002517839,0.00002754128,0.00001722137],"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":[0.00005151197,0.0000486758,0.000998597,0.00007198471,0.00002498629,0.0001174773,0.00009787949,0.9526355,0.01150287,0.007737093,0.0003981381,0.02631537],"study_design_scores_gemma":[0.000003300874,0.000007937664,0.0000407636,0.000001863026,0.000001132699,0.000008286946,0.000004722687,0.9982253,0.0006352164,0.0006535024,0.0004157804,0.000002157293],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0490229,0.0001683193,0.9467232,0.00009936135,0.00005541093,0.00005641207,0.00004114921,0.0005132585,0.003319932],"genre_scores_gemma":[0.7205878,0.0001690674,0.275209,0.0001218387,0.00005002211,0.0001770602,0.0001034595,0.0002011791,0.003380601],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002670342,"threshold_uncertainty_score":0.005309582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007277881631320184,"score_gpt":0.2107555241089199,"score_spread":0.2034776424775997,"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."}}