{"id":"W4409140933","doi":"10.1016/j.cam.2025.116659","title":"A discontinuous Galerkin method for a coupled Brinkman–Biot problem","year":2025,"lang":"en","type":"article","venue":"Journal of Computational and Applied Mathematics","topic":"Numerical methods in engineering","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Shaanxi Province; National Natural Science Foundation of China; Innovative Research Group Project of the National Natural Science Foundation of China; CMG Reservoir Simulation Foundation","keywords":"Mathematics; Biot number; Discontinuous Galerkin method; Galerkin method; Applied mathematics; Mathematical analysis; Calculus (dental); Finite element method; Mechanics","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":[0.000417693,0.0001173971,0.0003237262,0.0001152856,0.00003205533,0.00004239417,0.0000964151,0.00004349072,0.000003413308],"category_scores_gemma":[0.00004785713,0.00009959331,0.00006648785,0.0001340909,0.00001794445,0.00004340813,0.00002090683,0.0001392701,5.506914e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000028165,"about_ca_system_score_gemma":0.00001993567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":1.266937e-7,"about_ca_topic_score_gemma":7.277789e-8,"domain_scores_codex":[0.9992074,0.000005842419,0.0004643649,0.00006567946,0.0001368362,0.0001198694],"domain_scores_gemma":[0.9989325,0.000780245,0.0001092016,0.00004958675,0.00008028925,0.00004810894],"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":[0.00001770296,0.00006275754,0.000003058321,0.001029124,0.000198761,0.000001543726,0.000239591,0.8158146,0.005846746,0.1398318,0.0005383831,0.03641595],"study_design_scores_gemma":[0.0005381485,0.00002394395,0.00006546007,0.0001316785,0.00005463305,0.00003511406,0.00006400191,0.6972687,0.000780132,0.299644,0.001295692,0.00009842899],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005782102,0.0001919893,0.9921222,0.0001118399,0.0001242455,0.0002014787,0.000003330565,0.00004190487,0.001420948],"genre_scores_gemma":[0.03744832,0.00001103735,0.9623465,0.0000415044,0.00007016047,0.00001588107,9.881655e-7,0.00001808684,0.00004754527],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1598122,"threshold_uncertainty_score":0.4061297,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009887652926172332,"score_gpt":0.2779411022405019,"score_spread":0.2680534493143296,"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."}}