{"id":"W2085378537","doi":"10.1137/060661673","title":"A Preconditioner for Linear Systems Arising From Interior Point Optimization Methods","year":2007,"lang":"en","type":"article","venue":"SIAM Journal on Scientific Computing","topic":"Matrix Theory and Algorithms","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Preconditioner; Interior point method; Mathematics; Saddle point; Linear system; Applied mathematics; Eigenvalues and eigenvectors; Mathematical optimization; Matrix (chemical analysis); Iterated function; Condition number; Quadratic programming; Algorithm; Mathematical analysis; Geometry","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":[0.001538134,0.0008694929,0.0009643284,0.0004986226,0.0006148457,0.000801057,0.0008010578,0.00133511,0.004591378],"category_scores_gemma":[0.005892381,0.0004237573,0.0006227339,0.0006945847,0.001066237,0.0009602806,0.001832941,0.002741063,0.002528963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003095191,"about_ca_system_score_gemma":0.001120427,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009458524,"about_ca_topic_score_gemma":0.001107734,"domain_scores_codex":[0.9989308,0.000460272,0.00004435544,0.00008265156,0.0004130301,0.00006902056],"domain_scores_gemma":[0.9983513,0.0008930538,0.0001697407,0.0002641816,0.0002563705,0.00006536547],"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":[0.0002189715,0.0001538861,0.0006808329,0.0005901281,0.00007759759,0.0005228184,0.0004341738,0.5205763,0.03503006,0.2281516,0.009970653,0.203593],"study_design_scores_gemma":[0.00003231035,0.00006256491,0.00008572653,0.00003560543,0.00001020958,0.00008910264,0.00001786462,0.9543607,0.007360369,0.02905925,0.008871359,0.0000150241],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001625843,0.00007497636,0.9964834,0.00008710533,0.00003806207,0.00003227835,0.00002752521,0.0002972933,0.00133344],"genre_scores_gemma":[0.05325275,0.0002946222,0.9430901,0.0001029159,0.00008743809,0.0002802436,0.0001326837,0.0003248479,0.002434505],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004591378,"threshold_uncertainty_score":0.0153597,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03157416437652139,"score_gpt":0.346956663709278,"score_spread":0.3153824993327566,"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."}}