{"id":"W4411337578","doi":"10.1109/sp61157.2025.00256","title":"DPolicy: Managing Privacy Risks Across Multiple Releases with Differential Privacy","year":2025,"lang":"en","type":"article","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Differential privacy; Computer science; Information privacy; Internet privacy; Privacy protection; Computer security; Privacy software; Data mining","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":[0.02064327,0.001542695,0.001553308,0.002255025,0.00257489,0.007779164,0.006545575,0.003530742,0.004052461],"category_scores_gemma":[0.0505459,0.001911433,0.002606397,0.001743187,0.004434639,0.01696938,0.01958128,0.00720215,0.001616068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002758142,"about_ca_system_score_gemma":0.006696923,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005365454,"about_ca_topic_score_gemma":0.004660294,"domain_scores_codex":[0.9768568,0.00538791,0.002785733,0.004461559,0.00878402,0.00172406],"domain_scores_gemma":[0.9582168,0.01263228,0.003479543,0.02076961,0.003198692,0.001702948],"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":[0.00219788,0.0008473187,0.03381758,0.001407338,0.0007421833,0.001909815,0.006150954,0.08354777,0.03214968,0.3234272,0.06477696,0.4490253],"study_design_scores_gemma":[0.000434244,0.0004829972,0.003649902,0.0003647131,0.0002778995,0.00128236,0.0007655829,0.5537019,0.04628881,0.2209673,0.1713641,0.0004203256],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02519002,0.0007653321,0.9132435,0.001974568,0.0002270734,0.0008678827,0.0008808897,0.04988389,0.006966986],"genre_scores_gemma":[0.3634115,0.0006693103,0.6088738,0.002505552,0.0002790906,0.001236147,0.002966966,0.0083789,0.0116787],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02064327,"threshold_uncertainty_score":0.1091733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04122725779764052,"score_gpt":0.3260529797075011,"score_spread":0.2848257219098606,"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."}}