{"id":"W2925680367","doi":"10.48550/arxiv.1904.03615","title":"Topology of Pareto sets of strongly convex problems","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Precursory Research for Embryonic Science and Technology; Japan Society for the Promotion of Science","keywords":"Simplex; Mathematics; Pareto principle; Regular polygon; Mathematical optimization; Dimension (graph theory); Topology (electrical circuits); Multi-objective optimization; Convex analysis; Combinatorics; Convex optimization; 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"],"consensus_categories":[],"category_scores_codex":[0.0001507054,0.0002613947,0.0005549826,0.0002884753,0.00003698258,0.0000135283,0.001510713,0.0002787038,0.00003838867],"category_scores_gemma":[0.00003759925,0.0003082887,0.0001668163,0.0004709109,0.0002567874,0.0002946709,0.001690801,0.0003548733,0.00002227107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001370239,"about_ca_system_score_gemma":0.0002846562,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001004465,"about_ca_topic_score_gemma":0.00001416491,"domain_scores_codex":[0.9982885,0.0001416749,0.0003181201,0.0008730272,0.0001058156,0.000272931],"domain_scores_gemma":[0.9972928,0.0001321655,0.0007231407,0.001235819,0.0005264104,0.00008968542],"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":[0.00001518891,0.00009381307,0.003960977,0.0001341269,0.00008203738,0.00001965468,0.0002780782,0.9439536,0.00006904764,0.05105612,0.00002819695,0.0003091329],"study_design_scores_gemma":[0.0008501173,0.0001449719,0.001924114,0.00009886462,0.00003868889,0.000003470719,0.0001172758,0.98139,0.001068021,0.01390097,0.0001140802,0.0003494119],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03770809,0.00005008172,0.9591896,0.00003596754,0.0005774427,0.0004904228,0.00004266605,0.00008544326,0.001820298],"genre_scores_gemma":[0.9654375,0.00008412467,0.03369035,0.00001688773,0.00001611634,9.995092e-7,0.00001675724,0.00001644622,0.0007208656],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9277294,"threshold_uncertainty_score":0.9999369,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05769466798683245,"score_gpt":0.2086168239339704,"score_spread":0.1509221559471379,"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."}}