{"id":"W4414116218","doi":"10.2139/ssrn.5434274","title":"Meta Dynamic Pricing with Nonparametric Empirical Bayes","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Pooling; Regret; Nonparametric statistics; Dynamic pricing; Product (mathematics); Bayes' theorem; Parametric 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01326326,0.001439282,0.004689406,0.003583506,0.00122265,0.004894782,0.004000611,0.003857269,0.01206301],"category_scores_gemma":[0.05704524,0.003323249,0.00286426,0.003446495,0.002679989,0.008933149,0.003769292,0.005085856,0.00212615],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001525948,"about_ca_system_score_gemma":0.001935771,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003439045,"about_ca_topic_score_gemma":0.002883124,"domain_scores_codex":[0.9941771,0.003795041,0.0002977397,0.0006162683,0.0008209746,0.0002929149],"domain_scores_gemma":[0.9603624,0.03306805,0.001305053,0.003658298,0.001162249,0.0004439855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002948314,0.0002398462,0.001350957,0.0001820049,0.0003448403,0.0001862334,0.0001283888,0.4657108,0.0003650829,0.4436603,0.004125152,0.08341152],"study_design_scores_gemma":[0.0000295744,0.00001063101,0.00008754655,0.00001869162,0.00002165973,0.00003085172,0.000005400145,0.7763826,0.00006999089,0.2229161,0.0004134547,0.00001347675],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007970565,0.000560102,0.987837,0.0005383033,0.00008087023,0.00004867915,0.0001376536,0.0005002584,0.00232663],"genre_scores_gemma":[0.5122002,0.001590171,0.4650664,0.0006925843,0.001115656,0.0006069718,0.0009606442,0.000863971,0.01690331],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01326326,"threshold_uncertainty_score":0.07014364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02627151162049761,"score_gpt":0.2817050435551164,"score_spread":0.2554335319346188,"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."}}