{"id":"W3204390043","doi":"10.2139/ssrn.3930622","title":"Dynamic Pricing with Fairness Constraints","year":2021,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Dynamic pricing; Business; Economics; 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":[0.003966738,0.001066103,0.001960913,0.0009066932,0.001415803,0.005578409,0.003150798,0.002877099,0.01686971],"category_scores_gemma":[0.02074813,0.0009459844,0.0007657311,0.001947074,0.001949548,0.006330055,0.002422584,0.003887168,0.001780354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002289268,"about_ca_system_score_gemma":0.002040023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001566557,"about_ca_topic_score_gemma":0.0009975248,"domain_scores_codex":[0.9958857,0.001778009,0.000116305,0.0006080018,0.0008581709,0.0007537701],"domain_scores_gemma":[0.9922082,0.004817739,0.0004177866,0.001219691,0.0007946355,0.0005420148],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002281986,0.0002115455,0.000358128,0.00008390132,0.00004013225,0.0001748072,0.00007496983,0.1476086,0.00097037,0.8140267,0.00674312,0.02947961],"study_design_scores_gemma":[0.00005566885,0.00005011254,0.0001519476,0.00001632902,0.00002047468,0.0001395892,0.00003052752,0.5192601,0.0002953086,0.4771021,0.002856188,0.00002163756],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06116776,0.0006967493,0.8580068,0.003922665,0.00059891,0.0001548895,0.0002698114,0.0003478259,0.07483464],"genre_scores_gemma":[0.9240527,0.0003700109,0.04408005,0.0004164433,0.0004309077,0.0001192539,0.0001162636,0.0001216487,0.03029265],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01686971,"threshold_uncertainty_score":0.05643487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02952649317340615,"score_gpt":0.3764954576647959,"score_spread":0.3469689644913897,"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."}}