{"id":"W2030044614","doi":"10.1007/s11228-009-0112-5","title":"A Class of Quadratic Programs with Linear Complementarity Constraints","year":2009,"lang":"en","type":"article","venue":"Set-Valued and Variational Analysis","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Victoria","funders":"","keywords":"Complementarity (molecular biology); Complementarity theory; Quadratic equation; Mathematical optimization; Linear complementarity problem; Class (philosophy); Constraint (computer-aided design); Stationary point; Mixed complementarity problem; Mathematics; Independence (probability theory); Point (geometry); Applied mathematics; Computer science; Mathematical economics; Nonlinear system; Mathematical analysis; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.0003133689,0.0001270509,0.0003480888,0.0002207237,0.0001293028,0.00002854348,0.00009657005,0.00004410885,0.0003935313],"category_scores_gemma":[0.0001262251,0.0001005144,0.00008341319,0.001022352,0.0001379022,0.0001090873,0.00002252282,0.0001083082,0.000002117604],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000352872,"about_ca_system_score_gemma":0.00007694517,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003425467,"about_ca_topic_score_gemma":0.00007257581,"domain_scores_codex":[0.9985858,0.00009832164,0.0003662788,0.0002341605,0.0005360991,0.0001793651],"domain_scores_gemma":[0.9989913,0.0001767376,0.0001998633,0.0001808659,0.000361097,0.00009017875],"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":[0.0002610511,0.001607427,0.02557983,0.0001509674,0.004868406,0.0000131323,0.002371165,0.02886976,0.0002010893,0.9200454,0.0001429154,0.01588885],"study_design_scores_gemma":[0.001353716,0.0003040628,0.01412877,0.00002773672,0.001021673,0.000005503754,0.0004591107,0.9068798,0.00005185831,0.07548262,0.0000596738,0.0002254258],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03188924,0.00001625925,0.9661676,0.0006943714,0.000008300205,0.000367102,0.00009593728,0.00004454672,0.0007166619],"genre_scores_gemma":[0.6066574,0.000005003089,0.3928815,0.0000645,0.00002200059,0.00000879812,0.0002397101,0.000006022556,0.0001150442],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8780101,"threshold_uncertainty_score":0.4308892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06346052568580175,"score_gpt":0.3719427834021519,"score_spread":0.3084822577163501,"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."}}