{"id":"W4387048167","doi":"10.1117/12.3006741","title":"Eigenvalue solution of sparse matrix based on MPETSc","year":2023,"lang":"en","type":"article","venue":"","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Scalability; Sparse matrix; Supercomputer; Parallel computing; Eigenvalues and eigenvectors; Computational science; Field (mathematics); Software; Parallel processing; Parallel algorithm; Matrix (chemical analysis); Stability (learning theory); 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003150937,0.000523334,0.0006471725,0.0005953724,0.0005391239,0.0005645773,0.0006545684,0.0006576414,0.005055552],"category_scores_gemma":[0.001130123,0.0002068757,0.000449754,0.0007854489,0.0005149625,0.0006922071,0.0008384922,0.0006575258,0.001067978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002898479,"about_ca_system_score_gemma":0.00102735,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003840066,"about_ca_topic_score_gemma":0.004331175,"domain_scores_codex":[0.9997142,0.00005800492,0.00001095262,0.00003508402,0.0001488675,0.00003288345],"domain_scores_gemma":[0.9996386,0.0001203107,0.00002898314,0.00004239207,0.0001446964,0.00002515324],"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":[0.0001163664,0.0001075011,0.001372974,0.0003537245,0.00005111353,0.0005517117,0.0003180075,0.7257254,0.02287905,0.1041094,0.01010868,0.134306],"study_design_scores_gemma":[0.000005874255,0.0000113842,0.00008631455,0.00000548651,0.000002326278,0.00004411653,0.00001970665,0.9915237,0.001527462,0.005552814,0.001215249,0.000005501657],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01463811,0.000117441,0.9769928,0.0001780248,0.00007533797,0.00004704416,0.00007583232,0.0003864486,0.007488902],"genre_scores_gemma":[0.3366599,0.0004308425,0.649513,0.0001541714,0.0001211907,0.000267089,0.0003676922,0.0002476287,0.01223852],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005055552,"threshold_uncertainty_score":0.01691246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02176630387836509,"score_gpt":0.2677491288276375,"score_spread":0.2459828249492724,"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."}}