{"id":"W2143353673","doi":"10.1109/20.996093","title":"Combined direct-iterative matrix solvers for hierarchal vector finite elements","year":2002,"lang":"en","type":"article","venue":"IEEE Transactions on Magnetics","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Conjugate gradient method; Solver; Degrees of freedom (physics and chemistry); Finite element method; Krylov subspace; Matrix (chemical analysis); Iterative method; Computer science; Convergence (economics); Applied mathematics; Electromagnetics; Subspace topology; Reduction (mathematics); Algorithm; Mathematics; Mathematical optimization; Mathematical analysis; Physics; Geometry; Materials science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008864462,0.0006652821,0.0007029632,0.0006237758,0.0004252381,0.0007973603,0.001425629,0.001213437,0.006363526],"category_scores_gemma":[0.002663143,0.0004807294,0.0007127312,0.000910884,0.0004988254,0.0008877347,0.001410303,0.001058115,0.002874855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003812083,"about_ca_system_score_gemma":0.001180569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001882895,"about_ca_topic_score_gemma":0.004173224,"domain_scores_codex":[0.9990928,0.000235012,0.00004634794,0.00007016755,0.0005026204,0.00005309461],"domain_scores_gemma":[0.9987321,0.0004127263,0.0001027502,0.0002245782,0.0004651106,0.00006262243],"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":[0.0001688936,0.0002482946,0.001865453,0.000575463,0.0001422257,0.0002438502,0.000266328,0.5033138,0.03547242,0.08123787,0.009887299,0.3665781],"study_design_scores_gemma":[0.00003364592,0.00004985822,0.0001926163,0.00001851358,0.000009954142,0.00009724394,0.00002073917,0.9739153,0.008438732,0.007803962,0.009399732,0.00001965966],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004359442,0.0001177689,0.9898446,0.00005769396,0.00002765052,0.00007019542,0.00006270772,0.0007769173,0.004683128],"genre_scores_gemma":[0.08949166,0.0001395878,0.9034187,0.00006510953,0.0000290786,0.0002815569,0.0002223061,0.000258634,0.006093421],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006363526,"threshold_uncertainty_score":0.02128804,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02259434778564022,"score_gpt":0.2696922055764676,"score_spread":0.2470978577908273,"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."}}