{"id":"W2730291569","doi":"","title":"Solving Variational Inequalities with a Quadratic Cut Method: A Primal-Dual, Jacobian-Free Approach","year":2002,"lang":"en","type":"article","venue":"Les Cahiers du GERAD","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Group for Research in Decision Analysis; HEC Montréal","funders":"","keywords":"Jacobian matrix and determinant; Variational inequality; Mathematics; Quadratic equation; Variety (cybernetics); Dual (grammatical number); Mathematical optimization; Applied mathematics; Variational analysis; Geometry","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008779484,0.0003127618,0.000421753,0.0002649756,0.0004655816,0.0001651212,0.0003877152,0.000195812,0.0007079154],"category_scores_gemma":[0.002052961,0.0002692325,0.00008839914,0.000569843,0.0002548412,0.0004566421,0.0001105303,0.0005661098,0.00002862139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002937288,"about_ca_system_score_gemma":0.00008162905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002927519,"about_ca_topic_score_gemma":0.00001820996,"domain_scores_codex":[0.9971548,0.0004432485,0.0004934059,0.0004665097,0.000911104,0.0005309734],"domain_scores_gemma":[0.997108,0.001517857,0.0002368989,0.0006638647,0.0003034753,0.0001699287],"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":[0.0000796267,0.0005971717,0.0001705887,0.0004873881,0.000303716,0.00005663162,0.02601055,0.008756565,0.0001375937,0.9510247,0.008467279,0.003908244],"study_design_scores_gemma":[0.003206966,0.0002254759,0.0000759289,0.00008216104,0.0001099704,0.0002909182,0.00505632,0.7891405,0.0003238036,0.1979065,0.002623667,0.0009577803],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001993445,0.0001204226,0.9846717,0.0009502287,0.00004807053,0.000560606,0.00003543528,0.0002510367,0.01136908],"genre_scores_gemma":[0.005254911,0.0000457472,0.9844016,0.0002537921,0.0001995714,0.000182425,0.00003308415,0.00008997127,0.009538897],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.7803839,"threshold_uncertainty_score":0.999976,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06003866042478694,"score_gpt":0.3105596200361779,"score_spread":0.2505209596113909,"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."}}