{"id":"W4313591746","doi":"10.1109/jmmct.2022.3233944","title":"A Systematic Approach to Adaptive Mesh Refinement for Computational Electrodynamics","year":2023,"lang":"en","type":"article","venue":"IEEE journal on multiscale and multiphysics computational techniques","topic":"Computational Fluid Dynamics and Aerodynamics","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; National Aeronautics and Space Administration","keywords":"Adaptive mesh refinement; Computer science; Computational science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001080195,0.000548456,0.0005327709,0.0008525407,0.0005489903,0.0008029779,0.00144525,0.0008329442,0.001681176],"category_scores_gemma":[0.002277739,0.0004451333,0.001018757,0.000824798,0.001511073,0.0007708204,0.001763731,0.002425459,0.0007232095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005115606,"about_ca_system_score_gemma":0.0008400052,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009429178,"about_ca_topic_score_gemma":0.001263738,"domain_scores_codex":[0.9992531,0.0002651558,0.00004355008,0.00007390492,0.0003390379,0.00002518126],"domain_scores_gemma":[0.9994287,0.0001953363,0.00003783485,0.0001490339,0.000168652,0.00002037993],"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":[0.00002740892,0.00006165291,0.0006256616,0.0003811385,0.0001047612,0.00009027241,0.0001816227,0.1309792,0.01380363,0.6958278,0.004213728,0.1537032],"study_design_scores_gemma":[0.00003936383,0.00007636796,0.0004118739,0.0001832794,0.00003000554,0.0002104712,0.00003386062,0.6702238,0.005734628,0.2466239,0.07639251,0.00003994942],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003919575,0.0003890736,0.9976743,0.000125021,0.00006173085,0.00002305774,0.000009964564,0.00004751493,0.001277329],"genre_scores_gemma":[0.03876911,0.001571891,0.9551273,0.0002952421,0.000153956,0.0002728762,0.00006155905,0.0001198973,0.003628124],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001681176,"threshold_uncertainty_score":0.005712688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01411778013879554,"score_gpt":0.2534436607663798,"score_spread":0.2393258806275843,"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."}}