{"id":"W4241130888","doi":"10.23952/jano.1.2019.1.02","title":"DC-gap function and proximal methods for solving Nash-Cournot oligopolistic equilibrium models involving concave cost","year":2019,"lang":"en","type":"article","venue":"Journal of Applied and Numerical Optimization","topic":"Economic theories and models","field":"Economics, Econometrics and Finance","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Cournot competition; Oligopoly; Mathematical economics; Nash equilibrium; Economics; Symmetric equilibrium; Function (biology); Game theory; Equilibrium selection; Repeated game","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":[0.0008151516,0.0001472535,0.000517501,0.0001434485,0.00008232589,0.0001229151,0.00008176907,0.0001116797,0.00005329536],"category_scores_gemma":[0.00005408935,0.0001495279,0.00007907424,0.00007295204,0.00004618416,0.0004801799,0.00005000748,0.0001460166,0.000002792117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007352426,"about_ca_system_score_gemma":0.00002592817,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006111503,"about_ca_topic_score_gemma":1.04283e-7,"domain_scores_codex":[0.9987805,0.00001071284,0.0007161078,0.0002471798,0.00002779111,0.0002176763],"domain_scores_gemma":[0.9987804,0.0001894576,0.0007358936,0.00009997303,0.00007305575,0.0001211786],"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":[0.0003946365,0.00004089907,0.0002841391,0.00007205119,0.00007557572,1.854327e-7,0.0003260235,0.3605531,0.0005867509,0.6346843,0.00004930679,0.002933025],"study_design_scores_gemma":[0.001140966,0.0002018352,0.00008391127,0.00001659208,0.00002673757,0.000008169246,0.0001479111,0.7808084,0.00009147309,0.2166286,0.0006826393,0.0001627328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02640239,0.001179533,0.9676791,0.0001622595,0.0003997076,0.0003930458,0.00001590409,0.00001123255,0.003756755],"genre_scores_gemma":[0.8580387,0.0002990721,0.1411314,0.0002281221,0.0001801179,0.00001392284,0.000008202531,0.00002918615,0.00007123954],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8316363,"threshold_uncertainty_score":0.6097569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03618734998342756,"score_gpt":0.2626735323665416,"score_spread":0.226486182383114,"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."}}