{"id":"W3121333123","doi":"10.2139/ssrn.3685465","title":"Learning Product Rankings Robust to Fake Users","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Advanced Bandit Algorithms Research","field":"Decision Sciences","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"The Scarborough Hospital; University of Toronto","funders":"","keywords":"Product (mathematics); Computer science; Business; Econometrics; Marketing; Economics; Mathematics","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":["metaresearch","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.007553722,0.0002072749,0.0003474169,0.0003438584,0.0005526838,0.0004699252,0.001499421,0.00005440435,0.0002973606],"category_scores_gemma":[0.01044447,0.0001574525,0.0001703026,0.001960026,0.00007270551,0.0006328256,0.0002456759,0.004039685,0.001239104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006392659,"about_ca_system_score_gemma":0.001929857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001371904,"about_ca_topic_score_gemma":0.0001042457,"domain_scores_codex":[0.9926606,0.0003572507,0.0006148662,0.0006906486,0.002560324,0.003116244],"domain_scores_gemma":[0.9980487,0.0003722672,0.0002366023,0.0003056716,0.0005655769,0.0004712234],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005890058,0.00006864006,0.008244061,0.000005747291,0.0001699922,0.0000744819,0.003765468,0.2117924,0.003290416,0.004086647,0.00576995,0.7621432],"study_design_scores_gemma":[0.004963433,0.006564408,0.004583824,0.0000692471,0.00006420694,0.001852421,0.0401652,0.03013015,0.004253922,0.3642349,0.541183,0.001935326],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2289832,0.001485651,0.7269977,0.04058318,0.0004020512,0.0005021258,0.0000025675,0.0001364877,0.0009069677],"genre_scores_gemma":[0.9889696,0.0004382747,0.001925142,0.0006148319,0.001213682,0.000007590919,0.000001202258,0.00004531466,0.006784347],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7602079,"threshold_uncertainty_score":0.9995385,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08311210502914192,"score_gpt":0.3750910004815777,"score_spread":0.2919788954524358,"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."}}