{"id":"W2014632088","doi":"10.1137/s1052623499352632","title":"A Scaled Gauss--Newton Primal-Dual Search Direction for Semidefinite Optimization","year":2001,"lang":"en","type":"article","venue":"SIAM Journal on Optimization","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Overdetermined system; Symmetrization; Mathematics; Semidefinite programming; Interior point method; Linearization; Gauss; Mathematical optimization; Optimization problem; Applied mathematics; Combinatorics; Nonlinear system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00154215,0.0004074328,0.0004716639,0.0008352011,0.0008708586,0.0003884221,0.0002832364,0.000293302,0.000991335],"category_scores_gemma":[0.002047561,0.0003885828,0.0002301789,0.001238798,0.00009409701,0.001001221,0.0000678826,0.0006679682,0.00002986102],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006394419,"about_ca_system_score_gemma":0.0002252394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002551154,"about_ca_topic_score_gemma":0.000002207837,"domain_scores_codex":[0.9961624,0.0003712041,0.000987593,0.0005531907,0.00116124,0.0007643995],"domain_scores_gemma":[0.9962125,0.0008346906,0.0005327869,0.0004168359,0.001639858,0.0003633078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006759123,0.000348872,0.00007845336,0.00004893238,0.00006691424,0.00002006695,0.0001899514,0.9897994,0.00008155754,0.002475539,0.002081186,0.004133173],"study_design_scores_gemma":[0.003072081,0.0005898671,0.00002063,0.0001565943,0.0000554486,0.0003486741,0.0001748027,0.9892978,0.0005640031,0.002786503,0.002506592,0.0004269803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001182285,0.00007681404,0.9911462,0.001758333,0.0005053211,0.001274442,0.00002337618,0.0002640402,0.003769198],"genre_scores_gemma":[0.004993619,0.002225057,0.9832737,0.0002769424,0.0009815402,0.0001482046,0.0002355654,0.0002348474,0.00763054],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007872508,"threshold_uncertainty_score":0.9999219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07053505632736073,"score_gpt":0.3794270903251682,"score_spread":0.3088920339978075,"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."}}