{"id":"W4405172767","doi":"10.48550/arxiv.2412.05183","title":"Privacy Drift: Evolving Privacy Concerns in Incremental Learning","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Internet privacy; Information privacy; Computer science; Computer security; Business","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02737982,0.0008743235,0.001632312,0.0009958531,0.002484994,0.006415877,0.003847303,0.003644052,0.001199482],"category_scores_gemma":[0.12069,0.0008809118,0.001185857,0.001818458,0.006871493,0.01678964,0.007636097,0.006689581,0.0004177022],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002413076,"about_ca_system_score_gemma":0.002885148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009468207,"about_ca_topic_score_gemma":0.0006394501,"domain_scores_codex":[0.9704716,0.01526242,0.001444548,0.005101837,0.006447217,0.001272422],"domain_scores_gemma":[0.8755609,0.07188594,0.006852169,0.03939873,0.00492525,0.001376952],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007570798,0.0003001502,0.01713554,0.0005573446,0.0003228961,0.0006915668,0.003583247,0.1945029,0.008949231,0.5382314,0.005969188,0.2289996],"study_design_scores_gemma":[0.00004487118,0.0002141942,0.001332006,0.00009399758,0.00006437732,0.000693378,0.0003878072,0.3642684,0.008884278,0.6161433,0.007808839,0.00006453739],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05371803,0.001222888,0.9366261,0.004801055,0.0001037803,0.000107895,0.0001910903,0.0006181743,0.00261112],"genre_scores_gemma":[0.8753256,0.0006927172,0.1209136,0.00106691,0.0002411864,0.0001600785,0.0002047969,0.000167869,0.001227261],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02737982,"threshold_uncertainty_score":0.1448001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08476282742853636,"score_gpt":0.2339524782703339,"score_spread":0.1491896508417975,"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."}}