{"id":"W4416549440","doi":"10.1145/3719027.3744794","title":"Anonymity Unveiled: A Practical Framework for Auditing Data Use in Deep Learning Models","year":2025,"lang":"","type":"article","venue":"","topic":"Face recognition and analysis","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Deep learning; Audit; Anonymity; The Internet; Control (management); Training (meteorology)","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":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001944451,0.0003195171,0.0005550978,0.0005022953,0.0004583128,0.001500539,0.001291496,0.0003442154,0.000307661],"category_scores_gemma":[0.009114406,0.0003310198,0.0001967192,0.002284234,0.00009959802,0.004195457,0.001920668,0.001154223,0.00006291267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001152238,"about_ca_system_score_gemma":0.0004814474,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002155453,"about_ca_topic_score_gemma":0.0006108586,"domain_scores_codex":[0.9960117,0.0004910797,0.0008335346,0.001507623,0.0003847675,0.0007713406],"domain_scores_gemma":[0.9928221,0.00498859,0.0002826033,0.001411832,0.0003030892,0.0001917574],"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":[0.00009003048,0.0008525463,0.004999282,0.0002401624,0.0003450844,0.00006005631,0.0006103133,0.03971697,0.00002815061,0.5385969,0.001545005,0.4129156],"study_design_scores_gemma":[0.0005540863,0.00003937069,0.0001831625,0.0004026761,0.0001110999,0.000003827796,0.0005499494,0.9331775,0.0000558172,0.06269751,0.001892119,0.0003329028],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001652499,0.00016035,0.9874897,0.007270658,0.0003432089,0.0004371574,0.00002131451,0.0001281962,0.002496906],"genre_scores_gemma":[0.4373992,0.0002400418,0.5589067,0.00158057,0.00006819904,0.00002798051,0.00004599184,0.00001258511,0.001718796],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8934605,"threshold_uncertainty_score":0.9999142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.176728739864709,"score_gpt":0.377135799563907,"score_spread":0.200407059699198,"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."}}