{"id":"W4388626523","doi":"10.1016/j.jcp.2023.112631","title":"Numerical simulation of rarefied supersonic flows using a fourth-order maximum-entropy moment method with interpolative closure","year":2023,"lang":"en","type":"article","venue":"Journal of Computational Physics","topic":"Gas Dynamics and Kinetic Theory","field":"Mathematics","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Politecnico di Milano; Nvidia","keywords":"Moment closure; Supersonic speed; Knudsen number; Principle of maximum entropy; Entropy maximization; Solver; Statistical physics; Mechanics; Entropy (arrow of time); Physics; Mathematics; Classical mechanics; Applied mathematics; Mathematical optimization; Thermodynamics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004137822,0.0001402845,0.000369698,0.0001242635,0.00005010428,0.00002108682,0.0001122718,0.00004085049,0.00001642288],"category_scores_gemma":[0.00007435168,0.0001093682,0.000149171,0.0004471358,0.00003258172,0.0001325017,0.00002935157,0.0001995155,0.000001911026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008247315,"about_ca_system_score_gemma":0.0001520997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002379236,"about_ca_topic_score_gemma":3.022592e-7,"domain_scores_codex":[0.9985738,0.0001305849,0.0005003986,0.0001051494,0.0005455035,0.000144497],"domain_scores_gemma":[0.997551,0.0009963795,0.0006001272,0.00008839274,0.0007057979,0.00005833234],"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":[0.0002069391,0.0001375473,0.0001994526,0.00004710903,0.0002546153,0.00001085454,0.00167577,0.9748027,0.000324613,0.02124749,0.00002109469,0.001071794],"study_design_scores_gemma":[0.0006949526,0.0001885606,0.0003863123,0.00008314672,0.00006952673,0.00001962269,0.0001832099,0.6387998,0.0000612759,0.3594349,0.000008065942,0.00007059077],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4223717,0.000005375819,0.5773821,0.00007573715,0.00006009021,0.0000714815,0.000005203305,0.000007737279,0.00002051085],"genre_scores_gemma":[0.6921004,0.000001003922,0.307739,0.00001541698,0.0001087255,6.690938e-7,0.00000557858,0.00001979062,0.000009425289],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3381874,"threshold_uncertainty_score":0.4459907,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04238310221074669,"score_gpt":0.3484172701803465,"score_spread":0.3060341679695998,"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."}}