{"id":"W2054039722","doi":"10.1145/1806689.1806732","title":"Bayesian algorithmic mechanism design","year":2010,"lang":"en","type":"article","venue":"","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":115,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Incentive compatibility; Mechanism design; Incentive; Computer science; Mathematical optimization; Approximation algorithm; Compatibility (geochemistry); Mathematical economics; Strategic dominance; Bayesian probability; Nash equilibrium; Economics; Algorithm; Mathematics; Artificial intelligence; Microeconomics","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":[0.008697884,0.001089939,0.001570676,0.001349917,0.001063792,0.004351285,0.003169026,0.003557723,0.007366844],"category_scores_gemma":[0.02268188,0.001025357,0.001572365,0.00195256,0.003125888,0.006619273,0.003075883,0.003548597,0.001931078],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0019951,"about_ca_system_score_gemma":0.003264861,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006140168,"about_ca_topic_score_gemma":0.0008193721,"domain_scores_codex":[0.9922544,0.004287892,0.0003985119,0.0009277824,0.001821677,0.0003096747],"domain_scores_gemma":[0.9924148,0.004628018,0.000453118,0.001666609,0.0006529041,0.0001845524],"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":[0.00001433713,0.00003213621,0.00008940546,0.00009715751,0.00003353764,0.00001359302,0.00004191381,0.01745458,0.0001422814,0.9614841,0.001658554,0.01893834],"study_design_scores_gemma":[0.00003604844,0.00001933109,0.00003012957,0.00003534702,0.00001482141,0.00003135057,0.000009163351,0.06754615,0.0001878263,0.9248341,0.00724575,0.00001003095],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001625622,0.0004492585,0.9855292,0.001158067,0.00006741973,0.0001581508,0.00007113544,0.0001256893,0.0108155],"genre_scores_gemma":[0.1564452,0.001871407,0.828662,0.001069507,0.0003033773,0.001277856,0.0003033646,0.0001057296,0.00996155],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008697884,"threshold_uncertainty_score":0.04599935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09018186472496373,"score_gpt":0.3796185226475738,"score_spread":0.2894366579226101,"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."}}