{"id":"W188851899","doi":"","title":"Parallel implementation of AISM preconditioner for shifted linear systems of equations","year":2008,"lang":"en","type":"article","venue":"Conference on Scientific Computing","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Preconditioner; Computer science; Linear system; Applied mathematics; Parallel computing; Mathematics; Algorithm; Mathematical analysis; Iterative method","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":[0.0003492513,0.0006269839,0.0007219132,0.0005572973,0.0006248325,0.0006167422,0.001023085,0.0004878332,0.01687786],"category_scores_gemma":[0.0009999279,0.00029056,0.0004770106,0.0007141784,0.0003395139,0.0006139387,0.0009174263,0.0008105789,0.002685152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004961849,"about_ca_system_score_gemma":0.001295661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006741097,"about_ca_topic_score_gemma":0.0132585,"domain_scores_codex":[0.9996588,0.00005799114,0.00002421478,0.00004301036,0.0001471239,0.00006880841],"domain_scores_gemma":[0.9995363,0.00009261484,0.0000295166,0.0001179284,0.000181963,0.00004170535],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002204021,0.0004185525,0.003616664,0.0005688474,0.000192238,0.0005816351,0.0006304979,0.1825398,0.07236321,0.04295245,0.03583008,0.658102],"study_design_scores_gemma":[0.0002066269,0.000150081,0.0009495477,0.00002044063,0.00003174766,0.0001130608,0.0001101993,0.9430344,0.03130326,0.008699673,0.01535363,0.00002737717],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1342672,0.0004218669,0.822897,0.0005678529,0.0004718521,0.0001597786,0.000616746,0.01302211,0.02757571],"genre_scores_gemma":[0.4131452,0.0001930044,0.5670986,0.0001766181,0.0001231041,0.0001915943,0.001133096,0.000732132,0.01720666],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01687786,"threshold_uncertainty_score":0.05646205,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08990246772613014,"score_gpt":0.3351941745953493,"score_spread":0.2452917068692191,"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."}}