{"id":"W2972116450","doi":"10.1109/mwsym.2019.8701059","title":"A Stable Meshless Method for Electromagnetic Analysis","year":2019,"lang":"en","type":"article","venue":"","topic":"Numerical methods in engineering","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Regularized meshless method; Eigenvalues and eigenvectors; Interpolation (computer graphics); Moment (physics); Instability; Condition number; Matrix (chemical analysis); Meshfree methods; Mathematics; Sampling (signal processing); Numerical stability; Applied mathematics; Stability (learning theory); Numerical analysis; Method of moments (probability theory); Mathematical optimization; Singular boundary method; Computer science; Mathematical analysis; Finite element method; Physics; Mechanics; Engineering; Structural engineering; Classical mechanics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0002896535,0.0001363497,0.0003204328,0.0001882431,0.00001330372,0.00002289331,0.0001487086,0.00005663253,0.0005818401],"category_scores_gemma":[0.00003918471,0.0001293758,0.0001524323,0.0008293472,0.000003762562,0.00006554314,0.00001603531,0.00009485253,0.00004022617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005186578,"about_ca_system_score_gemma":0.000004810074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001061771,"about_ca_topic_score_gemma":0.000003340728,"domain_scores_codex":[0.999178,0.0000221005,0.0001721638,0.0001834665,0.00009860445,0.0003456579],"domain_scores_gemma":[0.9992577,0.0003455322,0.000011579,0.0002924961,0.00002593236,0.00006680167],"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":[0.000006880352,0.00001279797,0.0002909705,0.0001599559,0.0008393576,5.978549e-7,0.00004922909,0.7699648,0.1998598,0.004978407,0.0004157048,0.02342157],"study_design_scores_gemma":[0.0001696031,0.00004725904,0.000306925,0.000002615413,0.0002029248,9.453709e-7,0.0000157893,0.9620599,0.02918757,0.0007939165,0.007010336,0.0002022863],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01230186,0.0001589351,0.9740872,0.00001539352,0.0002092653,0.0002374733,0.000003870774,0.000492721,0.0124933],"genre_scores_gemma":[0.1009675,0.000007980363,0.8972001,0.00002911713,0.00003197365,0.00006342892,0.000003675715,0.00004285223,0.001653322],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.192095,"threshold_uncertainty_score":0.6370741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00790201531014331,"score_gpt":0.2737700980269712,"score_spread":0.2658680827168279,"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."}}