{"id":"W4408768736","doi":"10.23952/asvao.7.2025.2.01","title":"Relaxed inertial method for solving a class of bilevel variational inequalities","year":2025,"lang":"en","type":"article","venue":"Applied Set-Valued Analysis and Optimization","topic":"Contact Mechanics and Variational Inequalities","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Strong","keywords":"Class (philosophy); Inertial frame of reference; Variational inequality; Inequality; Mathematics; Bilevel optimization; Applied mathematics; Mathematical optimization; Computer science; Mathematical analysis; Artificial intelligence; Physics; Classical mechanics; Optimization problem","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001650193,0.0008958999,0.0009555679,0.0006281659,0.0003341113,0.0008124073,0.001533107,0.001175501,0.002577192],"category_scores_gemma":[0.002695134,0.0004453999,0.0008952577,0.000400842,0.001040836,0.001133732,0.00166655,0.001930105,0.0003675694],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004492433,"about_ca_system_score_gemma":0.0009015815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001344922,"about_ca_topic_score_gemma":0.001013811,"domain_scores_codex":[0.999477,0.0001975447,0.00002738689,0.00008028081,0.0001665598,0.00005124162],"domain_scores_gemma":[0.9993848,0.0003662281,0.00006101906,0.000050503,0.00009335859,0.00004406756],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001039414,0.0001015958,0.0006174967,0.0003148077,0.00007517206,0.0001468274,0.0002354821,0.7449246,0.01101684,0.1801796,0.0009789107,0.06130466],"study_design_scores_gemma":[0.000005493055,0.00002918081,0.00002929089,0.000006236093,0.000002647154,0.0000101578,0.000008004889,0.9932901,0.0004707787,0.00565108,0.0004930033,0.0000040248],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004436756,0.00008589948,0.9941346,0.00004624411,0.00001815038,0.00002538198,0.000009648809,0.00003141427,0.001212064],"genre_scores_gemma":[0.3688286,0.0004621712,0.6248873,0.0001592608,0.0001124372,0.000497335,0.0001519541,0.0001121211,0.004788741],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002577192,"threshold_uncertainty_score":0.008727193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02466143723198136,"score_gpt":0.2938490255023348,"score_spread":0.2691875882703535,"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."}}