{"id":"W4416510237","doi":"10.1016/j.orl.2025.107388","title":"A Frank-Wolfe algorithm for strongly monotone variational inequalities","year":2025,"lang":"en","type":"article","venue":"Operations Research Letters","topic":"Optimization and Variational Analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"European Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Variational inequality; Monotone polygon; Monotonic function; Inequality; Approximation algorithm","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.001298336,0.00009700756,0.000128326,0.0006293343,0.0008160909,0.0006993752,0.0005896682,0.00003922443,0.0001090044],"category_scores_gemma":[0.000337717,0.00009411182,0.00007966413,0.001296976,0.00006379908,0.0006753185,0.0001526603,0.0001634009,0.00003989886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001287279,"about_ca_system_score_gemma":0.0003693635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000263673,"about_ca_topic_score_gemma":0.00005316422,"domain_scores_codex":[0.998224,0.0002941187,0.0002861849,0.0003561031,0.0005373533,0.0003022022],"domain_scores_gemma":[0.9982489,0.0004973168,0.00001806264,0.0003584901,0.0008107533,0.00006647025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000003470121,0.00008377408,0.00004150074,0.000007251695,0.00009562795,9.003359e-7,0.0003476222,0.2086045,0.0006923514,0.769025,0.01496632,0.006131653],"study_design_scores_gemma":[0.0003860244,0.00002028611,0.0004347303,0.000007658379,0.000006062136,4.493053e-7,0.00006033339,0.9885922,0.0001840914,0.00115243,0.009062103,0.00009361728],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004175992,0.00002963046,0.9467638,0.05152204,0.0001331002,0.0003795967,0.00005069684,0.00005693753,0.0006466327],"genre_scores_gemma":[0.05354197,0.00002562753,0.9336235,0.004211022,0.0002072943,0.0008579753,0.0002771752,0.00001131034,0.00724411],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7799877,"threshold_uncertainty_score":0.6744092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0468969521409069,"score_gpt":0.3639787681576719,"score_spread":0.3170818160167651,"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."}}