{"id":"W3124137691","doi":"10.1016/s0167-2681(01)00173-1","title":"Why do biased heuristics approximate Bayes rule in double auctions?","year":2001,"lang":"en","type":"article","venue":"Journal of Economic Behavior & Organization","topic":"Auction Theory and Applications","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Heuristics; Common value auction; Bayes' theorem; Set (abstract data type); Mathematical economics; Bayesian probability; Economics; Econometrics; Computer science; Mathematics; Mathematical optimization; Microeconomics; Artificial intelligence","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":[0.00135455,0.0001110909,0.0002543062,0.0004848046,0.0001827193,0.000253585,0.0004054206,0.00008730466,0.003605126],"category_scores_gemma":[0.000233034,0.00008934062,0.00006982614,0.0006420702,0.00006154193,0.0007370279,0.0000450491,0.0001705036,0.0003733674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002110998,"about_ca_system_score_gemma":0.00007456279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001575224,"about_ca_topic_score_gemma":0.00001604475,"domain_scores_codex":[0.9982051,0.00008272391,0.001112715,0.0002124018,0.0002310151,0.0001560902],"domain_scores_gemma":[0.9984165,0.0001310308,0.0006504306,0.0002942838,0.0004073829,0.0001003624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003874356,0.002045032,0.8013461,0.000009593933,0.00006006221,0.00007706579,0.002717412,0.0530466,0.02907897,0.05548776,0.0265152,0.02922875],"study_design_scores_gemma":[0.01255625,0.0004862379,0.4262196,0.0001236577,0.0005591671,0.004281913,0.009876621,0.003717842,0.1124616,0.2472984,0.1804437,0.001975037],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.968558,0.00001997941,0.02908803,0.001167931,0.0006631347,0.000144619,0.000008476396,0.00001893048,0.0003308902],"genre_scores_gemma":[0.998131,0.00005233432,0.0008426011,0.0001199365,0.0002506514,0.000005905053,0.00001028648,0.00002012584,0.000567111],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3751266,"threshold_uncertainty_score":0.9973057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07862661267566036,"score_gpt":0.3566150309125754,"score_spread":0.2779884182369151,"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."}}