{"id":"W2526647779","doi":"10.2139/ssrn.2843112","title":"Bayesian Learning in Markets with Common Value.","year":2016,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Game Theory and Applications","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Bayesian probability; Value (mathematics); Econometrics; Computer science; Artificial intelligence; Economics; Statistics; Machine learning; Mathematics","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":[0.009333294,0.00113088,0.002729005,0.001324135,0.001213219,0.005325195,0.002384013,0.005181494,0.01002944],"category_scores_gemma":[0.05251897,0.001136142,0.001113683,0.001508017,0.004961682,0.01431955,0.002900059,0.004701352,0.0009923881],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003406691,"about_ca_system_score_gemma":0.002457749,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004914694,"about_ca_topic_score_gemma":0.004130842,"domain_scores_codex":[0.9940298,0.003531251,0.0002233876,0.0008307789,0.0007413544,0.0006435119],"domain_scores_gemma":[0.9639955,0.03060907,0.002249136,0.001012663,0.001074616,0.001059009],"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":[0.0001053893,0.00007918274,0.0008794852,0.0001402452,0.00009671345,0.0001448987,0.0001281214,0.05584506,0.0001682331,0.9230197,0.003340589,0.01605235],"study_design_scores_gemma":[0.00004061925,0.00002413188,0.0001978521,0.00002363701,0.00001596778,0.00003281491,0.00002968374,0.08463051,0.00004275311,0.9140092,0.00093699,0.00001592613],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07944579,0.006966118,0.8469431,0.01363972,0.0003071029,0.0002459263,0.0005287904,0.0002152282,0.05170827],"genre_scores_gemma":[0.923947,0.003681245,0.0527752,0.001021838,0.0006425958,0.000334039,0.0002115908,0.00008156166,0.01730498],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01002944,"threshold_uncertainty_score":0.0493598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0185979073125684,"score_gpt":0.3156986416808004,"score_spread":0.297100734368232,"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."}}