{"id":"W3085631657","doi":"10.1287/opre.2022.2380","title":"Learning Product Rankings Robust to Fake Users","year":2022,"lang":"en","type":"article","venue":"Operations Research","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Leverage (statistics); Computer science; Product (mathematics); Ranking (information retrieval); Analytics; Status quo; Data science; Learning to rank; Machine learning; Artificial intelligence; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008534339,0.001299772,0.002435482,0.001787569,0.000747224,0.002975901,0.001855197,0.002123634,0.001077423],"category_scores_gemma":[0.04612711,0.0007957667,0.0006579515,0.001309432,0.00221828,0.003746716,0.002104151,0.002674659,0.0007974515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00108253,"about_ca_system_score_gemma":0.001720205,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001961129,"about_ca_topic_score_gemma":0.001278571,"domain_scores_codex":[0.9963602,0.001551074,0.00027515,0.0007629485,0.0007469373,0.0003035707],"domain_scores_gemma":[0.9738962,0.01648036,0.003569098,0.00298769,0.002513312,0.000553477],"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":[0.0005078291,0.0002759906,0.009083519,0.0001550648,0.0001501668,0.0001715371,0.0001480511,0.843614,0.003138397,0.01655029,0.002847819,0.1233573],"study_design_scores_gemma":[0.000008155116,0.00003304079,0.0002741615,0.000004715311,0.000005083203,0.00001635931,0.00001013824,0.9930326,0.0005579185,0.005916986,0.0001342132,0.000006610906],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1279592,0.0005784385,0.8674878,0.001198529,0.00007373472,0.0001058556,0.0001830196,0.001001136,0.001412224],"genre_scores_gemma":[0.8640694,0.0002706385,0.132834,0.0002513335,0.000168374,0.0001192942,0.0005231838,0.0001014908,0.001662221],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008534339,"threshold_uncertainty_score":0.04513443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3625629463949137,"score_gpt":0.5291875609008896,"score_spread":0.1666246145059759,"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."}}