{"id":"W2913411363","doi":"10.1201/9781584888239-c32","title":"Convex Optimization","year":2009,"lang":"en","type":"book","venue":"Chapman & Hall/CRC applied algorithms and data structures series","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Conic optimization; Regular polygon; Mathematics; Mathematical optimization; Convex optimization; Computer science; Convex 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004205391,0.001150765,0.001404578,0.000406228,0.0005960545,0.0004851451,0.001729988,0.0009517605,0.0009713531],"category_scores_gemma":[0.0002218356,0.00108069,0.000100959,0.0002444608,0.0007728996,0.0008094524,0.001575348,0.001169163,0.00002394647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001975467,"about_ca_system_score_gemma":0.0004310498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007752312,"about_ca_topic_score_gemma":0.00002115641,"domain_scores_codex":[0.99498,0.00006097498,0.001008046,0.001950871,0.001139698,0.0008603592],"domain_scores_gemma":[0.9954808,0.0002662271,0.0007003805,0.002811648,0.0003271546,0.000413734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002487747,0.00009792626,9.106073e-7,0.001032328,0.0004947557,0.0000915261,0.000713999,0.00575615,0.00001533946,0.7799491,0.1141226,0.09747653],"study_design_scores_gemma":[0.001510183,0.0001793935,0.00001111154,0.0001625677,0.0002645374,0.0001941226,0.000301343,0.02915281,0.00007991918,0.7367321,0.2295854,0.001826545],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00000537889,0.003556251,0.6446726,0.0006868523,0.0006517398,0.003951259,0.00475185,0.001240143,0.3404839],"genre_scores_gemma":[0.00002079823,0.003972753,0.7921697,0.0003157208,0.001454585,0.00004925126,0.01492847,0.000357854,0.1867308],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1537531,"threshold_uncertainty_score":0.9999419,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06386492561833429,"score_gpt":0.3371041092670929,"score_spread":0.2732391836487586,"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."}}