{"id":"W3122287671","doi":"10.6082/bj5zh-3s548","title":"A complete characterization of equilibria in an intrinsic common agency screening game","year":2018,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Experimental Behavioral Economics Studies","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Mathematical economics; Sequential equilibrium; Equilibrium selection; Inefficiency; Characterization (materials science); Choice function; Bayesian game; Markov perfect equilibrium; Pooling; Economics; Delegation; Nash equilibrium; Solution concept; Mathematical optimization; Mathematics; Computer science; Repeated game; Microeconomics; Game theory; Physics","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":[0.002557134,0.0002651615,0.0007501753,0.0006428992,0.000209368,0.000157418,0.0009785284,0.0003942985,0.0001368321],"category_scores_gemma":[0.0001728626,0.00034367,0.0001211107,0.0002144773,0.001260384,0.0003762883,0.001606882,0.0008842431,0.0000100663],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00133624,"about_ca_system_score_gemma":0.0004161917,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00403114,"about_ca_topic_score_gemma":0.01629789,"domain_scores_codex":[0.9963959,0.0007906947,0.0009692098,0.0008020647,0.0002602448,0.0007818567],"domain_scores_gemma":[0.9983666,0.00020575,0.0004138106,0.0006995299,0.0001384003,0.0001758969],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004482596,0.0007918886,0.6078348,0.000196537,0.00009506305,0.00003377126,0.05553289,0.0002637649,0.04427117,0.003288471,0.000008149754,0.2872352],"study_design_scores_gemma":[0.002790723,0.0009765819,0.9411073,0.00162325,0.00003252046,0.000002884642,0.0169548,0.01078426,0.002933981,0.01213839,0.008290798,0.00236445],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9698767,0.00004720808,0.000001367634,0.0001662535,0.0003638435,0.001011747,0.0001228215,0.00003259831,0.02837747],"genre_scores_gemma":[0.996069,0.002650949,0.000355091,0.00002902356,0.0002621524,0.0001653205,0.000241423,0.00004804934,0.0001790076],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3332725,"threshold_uncertainty_score":0.9999015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.114442087518671,"score_gpt":0.4044755460034551,"score_spread":0.2900334584847841,"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."}}