{"id":"W3010781033","doi":"10.1016/j.jet.2020.105027","title":"Bayes and Hurwicz without Bernoulli","year":2020,"lang":"en","type":"article","venue":"Journal of Economic Theory","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Deutsche Forschungsgemeinschaft; Université Grenoble Alpes","keywords":"Ambiguity; Bernoulli's principle; Expected utility hypothesis; Certainty; Bayes' theorem; Subjective expected utility; Mathematical economics; Decision theory; Decision maker; Ambiguity aversion; Ranking (information retrieval); Mathematics; Computer science; Bayesian inference; Bayesian probability; Econometrics; Artificial intelligence; Operations research; Statistics","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":[0.003501382,0.000125575,0.0004879032,0.000159568,0.00007591366,0.0003047399,0.0006417906,0.00006872035,0.001378878],"category_scores_gemma":[0.001159815,0.00008958687,0.0001835931,0.00006173856,0.0001259545,0.0005402743,0.0001336169,0.0002171963,0.0005168104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004717623,"about_ca_system_score_gemma":0.0001140709,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001803708,"about_ca_topic_score_gemma":0.000003448822,"domain_scores_codex":[0.9982166,0.0001471765,0.001050367,0.0002549229,0.0001838318,0.0001471031],"domain_scores_gemma":[0.9973198,0.001220451,0.0008703152,0.0002268586,0.00008675648,0.0002758533],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000502289,0.00004758875,0.03773625,0.000003222704,0.00006703142,0.00005011409,0.001758211,0.0007609259,0.0004477453,0.01432277,0.01571022,0.9285936],"study_design_scores_gemma":[0.00105876,0.000422111,0.005272303,0.00003196178,0.00005787162,0.0003207428,0.00252975,0.001204216,0.000375232,0.8830495,0.1053956,0.0002819528],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9919081,0.0003852079,0.001181062,0.002166764,0.0006921135,0.00004201263,0.00001132712,0.000008409297,0.003604992],"genre_scores_gemma":[0.9970514,0.00006145158,0.001205874,0.0008854302,0.0004392533,3.256828e-7,1.642888e-7,0.00001331757,0.0003428547],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9283117,"threshold_uncertainty_score":0.999534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1443249202120448,"score_gpt":0.3975724710055006,"score_spread":0.2532475507934558,"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."}}