{"id":"W2144757184","doi":"10.1257/aer.20151743","title":"Discriminatory Information Disclosure","year":2017,"lang":"en","type":"article","venue":"American Economic Review","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":131,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of British Columbia","funders":"","keywords":"Valuation (finance); Private information retrieval; Mechanism design; Microeconomics; Economics; Complete information; Revenue; Information asymmetry; Object (grammar); Information design; Business; Actuarial science; Computer science; Finance; Artificial intelligence; Computer security","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001349678,0.00008372889,0.000296067,0.00004222116,0.0004235157,0.0002721459,0.001016313,0.00001194298,0.0008973382],"category_scores_gemma":[0.0007801159,0.00006058369,0.0001246194,0.00005121898,0.000445945,0.001403157,0.0001177166,0.00006298216,0.01039563],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003642268,"about_ca_system_score_gemma":0.00004635027,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004308245,"about_ca_topic_score_gemma":0.00001322043,"domain_scores_codex":[0.9989599,0.00007585699,0.0005384367,0.0001848486,0.0001317683,0.0001091815],"domain_scores_gemma":[0.9971752,0.0001391998,0.001160607,0.001403639,0.00004220861,0.00007915507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001386289,0.000004527026,0.001840528,0.00001537042,0.000005136174,8.748261e-8,0.00004050294,0.000003468519,7.970105e-7,0.04775984,0.03435729,0.915971],"study_design_scores_gemma":[0.00004295694,0.0000117238,0.03256243,0.00005893087,0.00001333082,0.00000454736,0.0002014878,0.00003751727,0.000009405138,0.01389897,0.9530614,0.00009729045],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1049459,0.009291453,0.01486282,0.08920065,0.001784286,0.001870795,0.0001963709,0.0001900474,0.7776577],"genre_scores_gemma":[0.9859111,0.008981397,0.0002268575,0.003043305,0.00009102345,0.00008018139,0.000008043767,0.000005525996,0.001652563],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9187041,"threshold_uncertainty_score":0.9903749,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08360790050604287,"score_gpt":0.4311653368776451,"score_spread":0.3475574363716022,"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."}}