{"id":"W4312500027","doi":"10.23952/asvao.4.2022.2.03","title":"Revisiting projection and contraction algorithms for solving variational inequalities and applications","year":2022,"lang":"en","type":"article","venue":"Applied Set-Valued Analysis and Optimization","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Contraction (grammar); Variational inequality; Algorithm; Computer science; Inequality; Mathematics; Applied mathematics; Mathematical analysis; Philosophy; Linguistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003292763,0.001806225,0.001603132,0.0008650779,0.0007372104,0.001526514,0.002127877,0.001988425,0.00250248],"category_scores_gemma":[0.007243577,0.0007854002,0.001565125,0.001719946,0.001998029,0.002953201,0.003554378,0.004405411,0.0008045289],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000673231,"about_ca_system_score_gemma":0.002589396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002282338,"about_ca_topic_score_gemma":0.001650844,"domain_scores_codex":[0.99832,0.0006727448,0.0001078718,0.0002601531,0.0005483862,0.00009083661],"domain_scores_gemma":[0.9981579,0.001117528,0.00009575015,0.0001677486,0.0003879035,0.00007308237],"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":[0.0001536305,0.0001706671,0.0006169484,0.0007945418,0.0001398515,0.0001992534,0.0004437212,0.4046134,0.01145174,0.264688,0.003759327,0.312969],"study_design_scores_gemma":[0.00001546002,0.00006263633,0.00004931737,0.00002522142,0.000009152137,0.00006322163,0.00001623566,0.9659457,0.001421002,0.02956944,0.002808913,0.00001373619],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001185862,0.0003624779,0.9974155,0.0001013822,0.00005239504,0.00002847235,0.000007537877,0.00004750044,0.0007988281],"genre_scores_gemma":[0.0764286,0.001544146,0.9181308,0.0002248113,0.0002456328,0.0003598624,0.00009300737,0.0001400499,0.00283296],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003292763,"threshold_uncertainty_score":0.01741403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04776065290182496,"score_gpt":0.3465372669410726,"score_spread":0.2987766140392477,"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."}}