{"id":"W3185315936","doi":"10.2478/popets-2021-0059","title":"You May Also Like... Privacy: Recommendation Systems Meet PIR","year":2021,"lang":"en","type":"article","venue":"Proceedings on Privacy Enhancing Technologies","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Computer science; Collusion; Protocol (science); Private information retrieval; Collaborative filtering; Consumption (sociology); Matrix decomposition; Theoretical computer science; Recommender system; Computer security; Information retrieval; Business","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007365309,0.0003938458,0.0004335181,0.0005031975,0.0003856503,0.0009332193,0.002449118,0.0003412437,0.00001463997],"category_scores_gemma":[0.001616006,0.0003769086,0.0001339757,0.001902037,0.0001112913,0.00157425,0.002465259,0.0005259401,0.00004913062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001431936,"about_ca_system_score_gemma":0.00009383918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001878769,"about_ca_topic_score_gemma":0.000004383284,"domain_scores_codex":[0.9970475,0.00002570569,0.0005860484,0.00120595,0.0004605894,0.000674205],"domain_scores_gemma":[0.9979596,0.0001485909,0.0003636586,0.00103316,0.0004134596,0.00008153719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002655885,0.0003709151,0.003068774,0.0003834463,0.00009921777,0.00002933286,0.001650497,0.000004817527,0.03580407,0.8364393,0.0303381,0.09178498],"study_design_scores_gemma":[0.0007138859,0.0003800963,0.0005900044,0.0005969584,0.00003484913,0.0001554196,0.0030153,0.004086185,0.6140738,0.1018202,0.273387,0.001146293],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.422738,0.002538025,0.4763065,0.05647428,0.003849169,0.001642356,0.00006532018,0.02456015,0.01182618],"genre_scores_gemma":[0.9246989,0.0004785664,0.07426761,0.0002714693,0.00006678382,0.0001297252,0.00002269145,0.00002766009,0.00003661189],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7346191,"threshold_uncertainty_score":0.9998683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02120760173932964,"score_gpt":0.258623653431808,"score_spread":0.2374160516924784,"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."}}