{"id":"W4410460921","doi":"10.1007/s10957-025-02691-8","title":"Adaptive Generalized Conditional Gradient Method for Multiobjective Optimization","year":2025,"lang":"en","type":"article","venue":"Journal of Optimization Theory and Applications","topic":"Advanced Multi-Objective Optimization Algorithms","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Perimeter Institute","funders":"","keywords":"Mathematics; Theory of computation; Mathematical optimization; Multi-objective optimization; Gradient method; Applied mathematics; Algorithm","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":[],"consensus_categories":[],"category_scores_codex":[0.000918651,0.0001722722,0.0002696782,0.0004140626,0.000410357,0.0001045477,0.0003340117,0.00008748664,0.00001952697],"category_scores_gemma":[0.000266479,0.0001635362,0.0001153282,0.0007157284,0.00009486084,0.0007818753,0.00007084598,0.000134049,6.642063e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001209734,"about_ca_system_score_gemma":0.0001680797,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":6.968365e-7,"about_ca_topic_score_gemma":2.460109e-7,"domain_scores_codex":[0.9985222,0.0002805834,0.0005552796,0.0003137394,0.0001679979,0.0001602654],"domain_scores_gemma":[0.9967806,0.0008756258,0.0006107686,0.0002236643,0.001413787,0.00009551625],"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":[0.00006609732,0.00007831497,0.000002370955,0.000005344495,0.00005588977,2.541674e-7,0.0001070385,0.5833791,0.00002495868,0.4103834,0.00005467234,0.005842602],"study_design_scores_gemma":[0.001562858,0.00008418294,0.00002362625,0.00002017981,0.00005979141,0.00002883589,0.0001792882,0.8972846,0.0005694708,0.09909286,0.0009532334,0.0001411081],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.000003114505,0.0002598919,0.9976756,0.0004756426,0.0001538099,0.0008669112,0.00002959362,0.00005181435,0.0004836442],"genre_scores_gemma":[0.002497497,0.0001677246,0.996031,0.0004853234,0.00009339147,0.0003063113,0.00003911427,0.00001366422,0.0003659441],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3139055,"threshold_uncertainty_score":0.6668811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01065066141948062,"score_gpt":0.312289075429338,"score_spread":0.3016384140098574,"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."}}