{"id":"W2814565151","doi":"10.1109/tmag.2018.2848622","title":"Matrix-Free Nodal Domain Decomposition With Relaxation For Massively Parallel Finite-Element Computation of EM Apparatus","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Magnetics","topic":"Electromagnetic Simulation and Numerical Methods","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Domain decomposition methods; Speedup; Massively parallel; Parallel computing; Computer science; Solver; Relaxation (psychology); Node (physics); Finite element method; Domain (mathematical analysis); Computational science; Nonlinear system; Algorithm; Physics; Mathematics","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":[0.0001166674,0.0001688305,0.0001833827,0.0001530459,0.0001067045,0.00002316514,0.00009798604,0.00009533757,0.00007521895],"category_scores_gemma":[0.000007600286,0.0001671524,0.00006597025,0.0002943803,0.00006490439,0.00006348327,7.616853e-7,0.0001199188,0.0000101488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005860736,"about_ca_system_score_gemma":0.00001836911,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003712114,"about_ca_topic_score_gemma":0.00001879733,"domain_scores_codex":[0.9990071,0.00005587426,0.0003395849,0.0001763806,0.0002097079,0.000211318],"domain_scores_gemma":[0.9992399,0.0002468264,0.00008495677,0.0001938607,0.0001654556,0.00006905929],"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":[0.0004059019,0.000132376,0.000008051316,0.00007084108,0.00004758997,6.332374e-7,0.0003919662,0.9438771,0.01427653,0.0002041016,0.000186137,0.04039878],"study_design_scores_gemma":[0.003042196,0.004831279,0.0008510386,0.00005370466,0.0001151799,0.000005871189,0.0001120644,0.9409998,0.0466131,0.002604526,0.000458049,0.0003131671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07342821,0.00003580741,0.9252741,0.00009154653,0.0002629283,0.0004782529,0.00003341816,0.0001302863,0.0002654752],"genre_scores_gemma":[0.6181556,0.00001458604,0.381613,0.00002519142,0.00004023863,0.00005253919,0.000009235186,0.00002487997,0.00006469501],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5447274,"threshold_uncertainty_score":0.6816276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01313178689626699,"score_gpt":0.2858313765943109,"score_spread":0.2726995896980439,"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."}}