{"id":"W2074560815","doi":"10.1016/s0096-3003(01)00096-0","title":"Parallel algorithms for solving tridiagonal and near-circulant systems","year":2002,"lang":"en","type":"article","venue":"Applied Mathematics and Computation","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Tridiagonal matrix; Circulant matrix; Tridiagonal matrix algorithm; Gaussian elimination; Algorithm; Mathematics; Linear system; System of linear equations; Coefficient matrix; Applied mathematics; Computer science; Gaussian; Mathematical analysis; Computational chemistry","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":[0.0007581724,0.0009265225,0.00098221,0.0008554628,0.001328768,0.001189398,0.001502435,0.001102674,0.006739293],"category_scores_gemma":[0.00461145,0.0005528021,0.0005513226,0.001754924,0.0007912879,0.001623745,0.001377025,0.001291602,0.001520107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006808797,"about_ca_system_score_gemma":0.001657592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004429968,"about_ca_topic_score_gemma":0.01130209,"domain_scores_codex":[0.9995009,0.0001337841,0.00003115722,0.00006896281,0.0001977613,0.00006743208],"domain_scores_gemma":[0.9984272,0.0007594165,0.000101647,0.0002469498,0.0003718989,0.00009294672],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003258591,0.0002641814,0.0006228975,0.0003375968,0.00009412341,0.0001723327,0.0002307798,0.5774891,0.006893019,0.1145081,0.01283644,0.2862257],"study_design_scores_gemma":[0.00005211536,0.0000262542,0.00006638181,0.000006904706,0.00001058353,0.00003293081,0.00002459317,0.9503445,0.001635729,0.04593584,0.001855702,0.000008471869],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01917729,0.0004558263,0.9725654,0.0002344885,0.0002101865,0.00007047923,0.00008930737,0.001068647,0.006128457],"genre_scores_gemma":[0.2046125,0.0004698891,0.7863563,0.0001556132,0.0001684999,0.0002804044,0.000284382,0.0003559173,0.007316445],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006739293,"threshold_uncertainty_score":0.02254516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03180460334454834,"score_gpt":0.2474985953858293,"score_spread":0.2156939920412809,"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."}}