{"id":"W4318332805","doi":"10.23952/jano.5.2023.1.09","title":"On the lower semicontinuity and subdifferentiability of the value function for conic linear programming problems","year":2023,"lang":"en","type":"article","venue":"Journal of Applied and Numerical Optimization","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Conic section; Mathematics; Linear programming; Value (mathematics); Mathematical optimization; Function (biology); Bellman equation; Applied mathematics; Geometry; Statistics","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":[0.0005209672,0.0000676606,0.0001414196,0.00005335157,0.0001381863,0.0000567939,0.0001418616,0.00003794908,0.000006255274],"category_scores_gemma":[0.0001049992,0.00003586351,0.00007107159,0.0004287814,0.00004058287,0.0001004567,0.00005481681,0.00008840184,2.859567e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000131158,"about_ca_system_score_gemma":0.00002805707,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001262331,"about_ca_topic_score_gemma":1.639678e-7,"domain_scores_codex":[0.9992719,0.00004414288,0.0002876796,0.0001169347,0.0001972626,0.00008212225],"domain_scores_gemma":[0.9990786,0.0002734853,0.0003301455,0.0001079353,0.0001756228,0.00003425329],"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":[0.00008969637,0.0001177497,0.0003081303,0.00002352338,0.00005743651,5.611119e-8,0.0002455408,0.902937,0.0002250224,0.09000441,0.00009802436,0.005893439],"study_design_scores_gemma":[0.0003172637,0.0001489495,0.00200799,0.00001328212,0.00004055909,0.00000109701,0.00002265806,0.9886801,0.0001323424,0.008396373,0.0001933574,0.00004601522],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02541055,0.00001127528,0.9722335,0.001934105,0.000104262,0.00024572,0.000001373813,0.00001322007,0.00004593205],"genre_scores_gemma":[0.9780653,0.00002917673,0.02165631,0.000171744,0.00003635578,0.00001005978,0.000002485993,0.000004472061,0.00002410664],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9526547,"threshold_uncertainty_score":0.1462471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01070490442645169,"score_gpt":0.2202832428924964,"score_spread":0.2095783384660447,"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."}}