{"id":"W3133973748","doi":"10.1145/3442188.3445864","title":"Price Discrimination with Fairness Constraints","year":2021,"lang":"en","type":"article","venue":"","topic":"Consumer Market Behavior and Pricing","field":"Business, Management and Accounting","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Science Foundation","keywords":"Price discrimination; Computer science; Microeconomics; Business; Economics","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":[0.0001100134,0.00008562331,0.0000852265,0.00006409189,0.00009368439,0.0002297043,0.00006537628,0.00002267149,0.003127279],"category_scores_gemma":[0.00003659,0.00006761248,0.00002423705,0.0003244301,0.0000450685,0.0005997096,0.00006650804,0.00005724902,0.0001099117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008014532,"about_ca_system_score_gemma":0.00002583401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000114186,"about_ca_topic_score_gemma":0.0002785546,"domain_scores_codex":[0.9994349,0.000004992177,0.00009788099,0.0001739567,0.0001467237,0.0001415343],"domain_scores_gemma":[0.9996076,0.00002587463,0.00004669668,0.0001302873,0.0001829236,0.00000662506],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005143809,0.0002230615,0.470371,0.0003224923,0.00004436894,0.0002519773,0.000132784,0.000007614018,0.003325331,0.1394442,0.002486924,0.3833389],"study_design_scores_gemma":[0.001512821,0.000007764756,0.91405,0.0001518667,0.0002772861,0.00005940965,0.003512627,0.0009028477,0.001760412,0.001688792,0.07535343,0.0007227586],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4404209,0.00002760034,0.009933046,0.001069884,0.0001884263,0.0001027422,6.617303e-7,0.0001473233,0.5481094],"genre_scores_gemma":[0.9967241,0.000001813398,0.0003704937,0.0007028444,0.0001176438,0.000006631808,0.00002461773,0.00001048944,0.002041387],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5563032,"threshold_uncertainty_score":0.997784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01970765413136193,"score_gpt":0.2296076847997862,"score_spread":0.2099000306684243,"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."}}