{"id":"W2116264034","doi":"10.1016/j.cam.2006.02.051","title":"Error analysis and preconditioning for an enhanced DtN-FE algorithm for exterior scattering problems","year":2006,"lang":"en","type":"article","venue":"Journal of Computational and Applied Mathematics","topic":"Electromagnetic Scattering and Analysis","field":"Physics and Astronomy","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Universities Space Research Association; National Science Foundation","keywords":"Mathematics; Finite element method; Perturbation (astronomy); Scattering; Boundary (topology); Boundary value problem; Algorithm; Dirichlet boundary condition; Mathematical analysis; Boundary element method; Numerical analysis; Neumann boundary condition; Geometry; Physics","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":[0.001698641,0.0007418636,0.0008378444,0.0005517603,0.0005298955,0.0008174466,0.001168723,0.001477845,0.004865688],"category_scores_gemma":[0.005928289,0.000319161,0.0005158797,0.0004846947,0.0008800765,0.001010566,0.001302206,0.001354015,0.0006861243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004842745,"about_ca_system_score_gemma":0.001205063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003574146,"about_ca_topic_score_gemma":0.005342097,"domain_scores_codex":[0.9994294,0.0002047952,0.00003837733,0.00005657129,0.0002361279,0.0000347574],"domain_scores_gemma":[0.9977697,0.0009596874,0.0001650465,0.0002788223,0.0007176039,0.0001091713],"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":[0.0005112466,0.0002220578,0.001347227,0.0003433277,0.00005289552,0.000282652,0.000303769,0.7143769,0.03041715,0.08053073,0.004360206,0.1672519],"study_design_scores_gemma":[0.000008785454,0.00001661666,0.00006547017,0.000006179182,0.00000280134,0.00001851771,0.000007111294,0.9953675,0.001387954,0.002318061,0.0007963101,0.000004649024],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0104907,0.00008541544,0.9869982,0.0001312785,0.0001037442,0.00003773854,0.00003799302,0.0001399253,0.001975018],"genre_scores_gemma":[0.1907462,0.0001791843,0.8012857,0.0001179309,0.00009932931,0.0001941529,0.0002088631,0.000357104,0.00681143],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004865688,"threshold_uncertainty_score":0.01627731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0099775646040196,"score_gpt":0.2531522167062571,"score_spread":0.2431746521022375,"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."}}