{"id":"W6903392782","doi":"10.1109/ccwc62904.2025.10903907","title":"Comparative Analysis of Differential Privacy Implementations on Synthetic Data","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":"Ontario Tech University","funders":"","keywords":"Differential privacy; Synthetic data; Information privacy; Implementation; Software; Noise (video); Differential (mechanical device); Privacy software","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":[0.02239354,0.0007556012,0.0009555685,0.001974891,0.0011872,0.002278841,0.001932092,0.001331728,0.001398916],"category_scores_gemma":[0.08317036,0.0003158371,0.0008674209,0.003295154,0.001990316,0.004227133,0.002955755,0.001778111,0.0003276827],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002294816,"about_ca_system_score_gemma":0.001589937,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002173426,"about_ca_topic_score_gemma":0.002200605,"domain_scores_codex":[0.9798575,0.01136465,0.001168609,0.001324895,0.005389953,0.000894349],"domain_scores_gemma":[0.9017558,0.07233588,0.002512903,0.01682012,0.005637922,0.0009373828],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003941995,0.001082426,0.02058326,0.001004524,0.0005864566,0.0004331379,0.0006315124,0.6396931,0.008208229,0.07082779,0.01576281,0.2372448],"study_design_scores_gemma":[0.0002098776,0.0008553955,0.004345275,0.00007955753,0.00005738686,0.0005596728,0.0004816305,0.9396304,0.01250243,0.03392126,0.007298894,0.00005824957],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.687337,0.003828725,0.2879655,0.002878254,0.00030487,0.0005806148,0.002577801,0.003102967,0.01142411],"genre_scores_gemma":[0.9105067,0.0005619071,0.08518166,0.0002639632,0.00003991833,0.0001756913,0.002302859,0.0001680295,0.0007992771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02239354,"threshold_uncertainty_score":0.1184298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09797837935623709,"score_gpt":0.3925088289229215,"score_spread":0.2945304495666844,"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."}}