{"id":"W2225794812","doi":"10.1609/aaai.v25i1.7865","title":"Efficiency and Privacy Tradeoffs in Mechanism Design","year":2011,"lang":"en","type":"article","venue":"Proceedings of the AAAI Conference on Artificial Intelligence","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Common value auction; Private information retrieval; Variety (cybernetics); Mechanism design; Dimension (graph theory); Mechanism (biology); Key (lock); Information privacy; Outcome (game theory); Differential privacy; Computer security; Data mining; Artificial intelligence; Microeconomics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.06466519,0.002132936,0.002872258,0.002722271,0.002395397,0.009205085,0.004477297,0.006407651,0.004844511],"category_scores_gemma":[0.175315,0.002180253,0.002548654,0.003175128,0.0110203,0.02772613,0.006614456,0.009108295,0.000956139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005663589,"about_ca_system_score_gemma":0.003626788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005684215,"about_ca_topic_score_gemma":0.000410892,"domain_scores_codex":[0.919734,0.05834179,0.0030687,0.005550086,0.01024459,0.003060774],"domain_scores_gemma":[0.7365273,0.223214,0.009030198,0.02369141,0.00584541,0.001691546],"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":[0.0002674789,0.0001204041,0.001009132,0.0002653858,0.0001364912,0.0001152743,0.000370073,0.05872431,0.0007124851,0.9154448,0.0009025671,0.02193174],"study_design_scores_gemma":[0.0001264449,0.0001633478,0.0002824682,0.00009250932,0.00005980574,0.0001826486,0.00009406377,0.06956968,0.001053753,0.9253925,0.002949996,0.00003276584],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03407876,0.0038429,0.9261228,0.01057657,0.0001504839,0.0003062867,0.0001384663,0.0001616298,0.02462213],"genre_scores_gemma":[0.7744523,0.003133973,0.2115768,0.001472598,0.0006499434,0.0009358024,0.0001704836,0.0002164554,0.007391762],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06466519,"threshold_uncertainty_score":0.3419863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3936472202184486,"score_gpt":0.3766836790165272,"score_spread":0.01696354120192145,"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."}}