{"id":"W4393443251","doi":"10.23952/jano.6.2024.2.07","title":"On approximate positively properly efficient solutions in nonsmooth semi-infinite multiobjective optimization problems with data uncertainty","year":2024,"lang":"en","type":"article","venue":"Journal of Applied and Numerical Optimization","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Mathematical optimization; Multi-objective optimization; Mathematics; Applied mathematics; Computer science","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":[0.0005468505,0.00018571,0.0002746526,0.0004750416,0.0001540909,0.0003467727,0.0003471297,0.00007266368,0.00001745389],"category_scores_gemma":[0.00005026386,0.000130379,0.00004214176,0.001351866,0.00004841489,0.0006115285,0.0001190778,0.000257333,0.000002656219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001641448,"about_ca_system_score_gemma":0.000195997,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001403249,"about_ca_topic_score_gemma":0.000001424422,"domain_scores_codex":[0.9983376,0.00007401747,0.0005042068,0.0004321709,0.0004420093,0.0002099913],"domain_scores_gemma":[0.9989405,0.0001790457,0.0002655679,0.0002358821,0.000268781,0.0001102181],"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":[0.0001120056,0.0002126088,0.00001082509,0.00002059681,0.00006260918,0.000007370732,0.0005410002,0.97372,0.00002379247,0.02325174,0.00003622682,0.002001243],"study_design_scores_gemma":[0.0006780764,0.0002320461,0.00008456806,0.0001323082,0.0000497184,0.00002542245,0.00005356152,0.998199,0.00001254407,0.0002921081,0.0000669845,0.0001736487],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002528526,0.00008478136,0.9969543,0.00124346,0.00007626862,0.0002937086,0.00001560078,0.0000527685,0.00102627],"genre_scores_gemma":[0.6314337,0.0001138422,0.3680245,0.000238226,0.00005228087,0.00001632142,0.00008230767,0.00001930528,0.000019432],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6311809,"threshold_uncertainty_score":0.5316702,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01607393967970721,"score_gpt":0.2352659826367703,"score_spread":0.219192042957063,"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."}}