{"id":"W3005428264","doi":"10.3982/te2818","title":"Information design and sequential screening with ex post participation constraint","year":2020,"lang":"en","type":"article","venue":"Theoretical Economics","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"HEC Montréal","funders":"","keywords":"Mechanism design; Principal (computer security); Computer science; Economic rent; Constraint (computer-aided design); Participation constraint; Mechanism (biology); Profit (economics); Mathematical optimization; Ex-ante; Mathematical economics; Artificial intelligence; Microeconomics; Economics; Mathematics; Computer security; Incentive","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0130023,0.001737038,0.003323544,0.00113776,0.001113057,0.003220284,0.003867712,0.005102016,0.01257859],"category_scores_gemma":[0.03552673,0.001442539,0.001474874,0.001624198,0.003573273,0.00655421,0.002053345,0.003261636,0.001455285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002553176,"about_ca_system_score_gemma":0.003530222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002216387,"about_ca_topic_score_gemma":0.001296519,"domain_scores_codex":[0.9887664,0.006527012,0.000516159,0.001710861,0.001136618,0.001342962],"domain_scores_gemma":[0.9489769,0.03618178,0.00779625,0.00327871,0.002173053,0.001593221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007339019,0.0004976963,0.00195674,0.0004066589,0.0001773856,0.0009141993,0.0003729058,0.1894242,0.001974292,0.7796311,0.002700188,0.02121065],"study_design_scores_gemma":[0.0006719291,0.0003945501,0.0004816187,0.00004585365,0.00006071621,0.0002127391,0.00006959614,0.4518434,0.0008926612,0.5427644,0.002495725,0.00006676809],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1212769,0.0007973157,0.8461195,0.004877287,0.0001468147,0.0006984966,0.0007353353,0.0003194502,0.02502895],"genre_scores_gemma":[0.9117207,0.0006666211,0.06453104,0.0004901612,0.0001847903,0.0007802725,0.0002651863,0.00005163847,0.02130957],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0130023,"threshold_uncertainty_score":0.06876349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08621763586449831,"score_gpt":0.3218474511972208,"score_spread":0.2356298153327225,"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."}}