{"id":"W3123764657","doi":"","title":"Equilibrium Selection in Experimental Cheap Talk Games","year":2015,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Ludwig-Maximilians-Universität München; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Universiteit van Amsterdam; York University; National Science Foundation","keywords":"Stability (learning theory); Equilibrium selection; Mathematical economics; Selection (genetic algorithm); Range (aeronautics); Cheap talk; Economics; Measure (data warehouse); Extensive-form game; Computer science; Econometrics; Game theory; Repeated game; Engineering; Artificial intelligence; Data mining; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.02273853,0.0009354696,0.00140669,0.001173305,0.0009068897,0.002024411,0.001633871,0.001410159,0.002558828],"category_scores_gemma":[0.09943876,0.000680037,0.0009648436,0.0007044452,0.003684881,0.00325323,0.002019449,0.00190883,0.0003089389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001720358,"about_ca_system_score_gemma":0.0007301025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001234122,"about_ca_topic_score_gemma":0.0009893993,"domain_scores_codex":[0.9840641,0.01107144,0.0007138298,0.001575786,0.00212164,0.0004532303],"domain_scores_gemma":[0.9316455,0.04869756,0.007151127,0.00929542,0.002239206,0.0009712384],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002923357,0.0008529883,0.02269799,0.0006175604,0.0006129044,0.000190945,0.002423786,0.1910389,0.01931234,0.712828,0.002322914,0.04417829],"study_design_scores_gemma":[0.0005395859,0.0008543614,0.007734029,0.00006145148,0.00009415064,0.00008986051,0.0002895302,0.3700903,0.009128745,0.6095037,0.001489798,0.0001243435],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6376728,0.000258287,0.3500631,0.000745372,0.00005647581,0.0003909008,0.0003172412,0.0003537172,0.01014213],"genre_scores_gemma":[0.9528587,0.0000666534,0.04540458,0.0001560612,0.00002335608,0.0004821538,0.0001637866,0.00004017609,0.0008044212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02273853,"threshold_uncertainty_score":0.1202543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08174657596010759,"score_gpt":0.4099839634709326,"score_spread":0.328237387510825,"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."}}