{"id":"W1961233311","doi":"10.1109/mwscas.1993.343095","title":"PCG techniques for interior point algorithms","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Conjugate gradient method; Bottleneck; Computer science; Simplex algorithm; Algorithm; Point (geometry); Simplex; Interior point method; Focus (optics); Mathematical optimization; Linear programming; Mathematics; Combinatorics; 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":[0.001844633,0.001932699,0.001408005,0.001641591,0.001022313,0.001419018,0.001591214,0.001892622,0.0122263],"category_scores_gemma":[0.007781744,0.001002156,0.001315303,0.002441192,0.002196169,0.001772763,0.002963843,0.004243583,0.006044737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009716455,"about_ca_system_score_gemma":0.001669467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003773337,"about_ca_topic_score_gemma":0.003727826,"domain_scores_codex":[0.9983696,0.0006335419,0.00007036274,0.0001699194,0.0006741246,0.00008245126],"domain_scores_gemma":[0.9983684,0.0009025219,0.00009571254,0.0002813519,0.0003066703,0.00004530161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009215793,0.00007804325,0.0003597397,0.0004954105,0.00007832338,0.0001422298,0.0002273392,0.2265438,0.002880874,0.5003546,0.01615924,0.2525882],"study_design_scores_gemma":[0.00005834983,0.00004295431,0.00007775144,0.00009608724,0.00001995923,0.0001029122,0.00003255387,0.6590077,0.00185837,0.2893611,0.04932157,0.0000206897],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003895525,0.0004815168,0.9947743,0.0001439066,0.00009807946,0.00005270413,0.00003495304,0.0003651406,0.003659758],"genre_scores_gemma":[0.03234803,0.001492701,0.9562243,0.0003670059,0.0002324384,0.0006332289,0.0002306166,0.0008938555,0.007577779],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0122263,"threshold_uncertainty_score":0.04090106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1029855071443713,"score_gpt":0.3897434070037726,"score_spread":0.2867578998594014,"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."}}