{"id":"W4226394830","doi":"10.23952/jano.4.2022.1.08","title":"Optimality and duality for semidefinite multiobjective programming problems using convexificators","year":2022,"lang":"en","type":"article","venue":"Journal of Applied and Numerical Optimization","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Science and Engineering Research Board","keywords":"Duality (order theory); Semidefinite programming; Mathematical optimization; Semidefinite embedding; Multiobjective programming; Mathematics; Strong duality; Multi-objective optimization; Mathematical economics; Computer science; Combinatorics; Optimization problem; Quadratically constrained quadratic program; Quadratic programming","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006819538,0.00009765184,0.0002282396,0.0001404172,0.0003733571,0.000123215,0.0001316537,0.00003140995,0.00001161116],"category_scores_gemma":[0.00004428767,0.00008884734,0.00006043295,0.0004174595,0.00003217217,0.0002822975,0.0001116942,0.0001272418,7.315082e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006244694,"about_ca_system_score_gemma":0.0000636299,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005073103,"about_ca_topic_score_gemma":5.345548e-8,"domain_scores_codex":[0.9989295,0.00006623696,0.0004185437,0.0002061996,0.0002575561,0.0001219874],"domain_scores_gemma":[0.9989707,0.0001336912,0.0005143792,0.00008073698,0.0002052811,0.00009514311],"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":[0.00005927252,0.00009548934,0.0002706454,0.00001458542,0.00004772083,4.671616e-7,0.0006947776,0.9806333,0.00008406835,0.01483545,0.0000106908,0.00325352],"study_design_scores_gemma":[0.000647297,0.0001211188,0.0002143854,0.000003499362,0.00004447538,0.00002295986,0.0002268513,0.9966426,0.00004056204,0.001404108,0.0005213661,0.0001106984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002816913,0.00005935306,0.9963113,0.0004304391,0.00006554686,0.0002255369,0.000005584939,0.00001814443,0.00006719963],"genre_scores_gemma":[0.436964,0.00001804405,0.5628082,0.0001496282,0.00002636098,0.00001690403,0.000006526123,0.000005689628,0.000004652084],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4341471,"threshold_uncertainty_score":0.3623089,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02250132360065009,"score_gpt":0.2564471490728111,"score_spread":0.233945825472161,"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."}}