{"id":"W2333353949","doi":"10.2514/6.2005-5035","title":"Numerical Modeling of Micron-Scale Flows Using the Gaussian Moment Closure","year":2005,"lang":"en","type":"article","venue":"35th AIAA Fluid Dynamics Conference and Exhibit","topic":"Gas Dynamics and Kinetic Theory","field":"Mathematics","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Innovation Trust","keywords":"Knudsen number; Closure (psychology); Gaussian; Finite volume method; Moment (physics); Mechanics; Boundary value problem; Flow (mathematics); Moment closure; Cylinder; Mathematics; Applied mathematics; Physics; Statistical physics; Mathematical analysis; Classical mechanics; Turbulence; Geometry","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":[0.0004289298,0.0002757942,0.0004153374,0.0000781327,0.0001716922,0.00007076593,0.0002952925,0.0001491168,0.0000789099],"category_scores_gemma":[0.00002614654,0.0002041849,0.0001244052,0.0001361164,0.0001255351,0.00009656895,0.0001355347,0.0002620081,0.000004828324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000819843,"about_ca_system_score_gemma":0.00009079868,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009902345,"about_ca_topic_score_gemma":0.0001935802,"domain_scores_codex":[0.9983618,0.00007651842,0.0005471332,0.0003377907,0.0002735215,0.0004031892],"domain_scores_gemma":[0.9990095,0.00009269716,0.0001449095,0.0004892416,0.0001372214,0.0001264132],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001770344,0.0005565066,0.002557471,0.0003964481,0.0002149785,0.00001076039,0.006419671,0.07239976,0.01653695,0.8833784,0.0001522377,0.01719981],"study_design_scores_gemma":[0.0003905242,0.00005635179,0.00004667564,0.0001068174,0.00007483506,0.00003015452,0.0006853075,0.9655688,0.0002077311,0.03249608,0.0001054166,0.0002312444],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7344643,0.0001771796,0.2625808,0.0007266284,0.00008443218,0.0002300726,0.00002927057,0.00003074062,0.001676639],"genre_scores_gemma":[0.9765183,0.0001257648,0.02285972,0.0001010576,0.00009656818,0.000009398329,0.00001346098,0.0000364857,0.0002392389],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8931691,"threshold_uncertainty_score":0.832642,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03062133277558454,"score_gpt":0.2740472679383485,"score_spread":0.243425935162764,"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."}}