{"id":"W4412767577","doi":"10.23952/jano.7.2025.2.03","title":"Strong convergence of an inertial Tseng’s extragradient algorithm for pseudomonotone variational inequalities with applications to optimal control problems","year":2025,"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":"Centre Scientifique et Technique du Bâtiment; Fundamental Research Funds for the Central Universities; Natural Science Foundation of Chongqing","keywords":"Variational inequality; Inertial frame of reference; Convergence (economics); Algorithm; Mathematics; Applied mathematics; Computer science; Physics; Economics","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":[0.0003886236,0.0001265809,0.0003129706,0.0002697929,0.0001184954,0.00008001816,0.0002498853,0.00005224656,0.00001200946],"category_scores_gemma":[0.00002376958,0.0001022136,0.00005767332,0.0005914856,0.00003537249,0.0003519871,0.00003183006,0.00007624037,2.60012e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004153359,"about_ca_system_score_gemma":0.0001723564,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006785075,"about_ca_topic_score_gemma":4.953826e-7,"domain_scores_codex":[0.9987198,0.00004181622,0.0006043347,0.0002176555,0.0002820777,0.0001343371],"domain_scores_gemma":[0.9984837,0.0001597541,0.0004363177,0.0001321472,0.0006623241,0.0001257332],"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":[0.0001112967,0.0001706653,0.00002309838,0.00001353746,0.00009087938,1.6582e-7,0.0002616243,0.8597333,0.000169992,0.1306852,0.00001587182,0.008724398],"study_design_scores_gemma":[0.001354278,0.0003090439,0.0001993497,0.00001513575,0.00007607665,0.000004339131,0.00008696911,0.9963589,0.0002366443,0.0009775053,0.0002688411,0.0001128928],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0002755285,0.00002287217,0.9982303,0.0008096833,0.00005577051,0.0004657377,0.00001901261,0.00001580804,0.0001052543],"genre_scores_gemma":[0.2487663,0.00001304256,0.7508178,0.0002142544,0.00005935549,0.00008210836,0.00001897735,0.000005624132,0.0000226186],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2484907,"threshold_uncertainty_score":0.4168149,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00856190637897728,"score_gpt":0.2455630026663448,"score_spread":0.2370010962873676,"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."}}