{"id":"W4234891635","doi":"10.23952/jnva.4.2020.3.05","title":"Efficiency conditions for multiobjective bilevel programming problems via convexificators","year":2020,"lang":"en","type":"article","venue":"Journal of Nonlinear and Variational Analysis","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Foundation for Science and Technology Development","keywords":"Bilevel optimization; Multiobjective programming; Mathematical optimization; Multi-objective optimization; Computer science; Mathematics; Optimization problem","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007016588,0.002396309,0.00188544,0.001973811,0.0008843502,0.003219754,0.001398861,0.001631851,0.007498882],"category_scores_gemma":[0.01520472,0.001163461,0.002047434,0.001466609,0.002822064,0.004234506,0.003459935,0.003529342,0.001231549],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001797417,"about_ca_system_score_gemma":0.002328235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001455268,"about_ca_topic_score_gemma":0.001167342,"domain_scores_codex":[0.9973194,0.001191284,0.0001820787,0.0003423867,0.0006286209,0.0003363822],"domain_scores_gemma":[0.9936336,0.004582199,0.0004040998,0.0002467931,0.000938338,0.0001948842],"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":[0.000113487,0.00009556661,0.0003826892,0.0004762244,0.00008664573,0.0002087231,0.0003150533,0.2526409,0.005307849,0.712352,0.003356278,0.02466454],"study_design_scores_gemma":[0.0000484872,0.0001266501,0.0003303925,0.0001753885,0.00003726765,0.00007356223,0.0001405359,0.6418967,0.003910288,0.3488145,0.004403578,0.00004260729],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01331851,0.0005805166,0.9709608,0.0004808667,0.0000555277,0.0001164764,0.0001355003,0.00007788298,0.0142739],"genre_scores_gemma":[0.6999586,0.003344569,0.2733574,0.0003868102,0.0002261899,0.001466541,0.0008103789,0.0004970822,0.0199525],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007498882,"threshold_uncertainty_score":0.03710771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0232271809863033,"score_gpt":0.2721182565099743,"score_spread":0.248891075523671,"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."}}