{"id":"W4401816663","doi":"10.1016/j.jcp.2024.113364","title":"Hybridized formulations of flux reconstruction schemes for advection-diffusion problems","year":2024,"lang":"en","type":"article","venue":"Journal of Computational Physics","topic":"Advanced Numerical Methods in Computational Mathematics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Alliance de recherche numérique du Canada; Concordia University","keywords":"Advection; Diffusion; Flux (metallurgy); Applied mathematics; Mathematics; Physics; Mathematical analysis; Statistical physics; Mechanics; Computer science; Geometry; Calculus (dental); Materials science; Thermodynamics; Medicine","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":[0.0001951014,0.0001092392,0.0002378798,0.00013313,0.00004745315,0.0000250679,0.0000768192,0.00003494644,0.000009569175],"category_scores_gemma":[0.0001200884,0.0001020608,0.0001833492,0.0003107282,0.00003700109,0.0003710844,0.00001036742,0.00014877,0.000002468097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007982308,"about_ca_system_score_gemma":0.00007091522,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.116287e-7,"about_ca_topic_score_gemma":3.291666e-8,"domain_scores_codex":[0.9989212,0.00001930121,0.0006158489,0.00007638372,0.0002767423,0.00009058939],"domain_scores_gemma":[0.9979777,0.001228383,0.0002015078,0.00005141646,0.0005002839,0.00004065011],"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":[0.00001111174,0.00003200995,0.000007928746,0.0003708314,0.00009689756,3.979636e-7,0.0001009274,0.8566003,0.00238879,0.03802912,0.0001898599,0.1021718],"study_design_scores_gemma":[0.000177722,0.00004573514,0.00003332682,0.0001655453,0.00002504449,0.00004029119,0.00001032372,0.5019345,0.001515922,0.4953566,0.0006400129,0.00005502253],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03270378,0.000275501,0.965654,0.00005145583,0.0008920372,0.0001594285,0.00001823536,0.00006518605,0.0001803609],"genre_scores_gemma":[0.3992087,0.00001134373,0.6004275,0.000005446932,0.0002988101,0.000005865914,0.000009736113,0.00002184976,0.00001077888],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4573275,"threshold_uncertainty_score":0.4161918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02594721153958353,"score_gpt":0.307972796492841,"score_spread":0.2820255849532575,"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."}}