{"id":"W4410204358","doi":"10.1109/tdsc.2025.3568160","title":"On Estimating the Strength of Differentially Private Mechanisms in a Black-Box Setting","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Dependable and Secure Computing","topic":"Metallurgy and Material Forming","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute","funders":"European Commission","keywords":"Black box; Computer science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002460468,0.0001595618,0.0002111634,0.0001516169,0.0001776128,0.00004387215,0.0001175331,0.00007595308,0.0000251944],"category_scores_gemma":[0.000009174759,0.0001292384,0.00005068915,0.0001952961,0.0000240637,0.00006368123,0.000004108619,0.0002931027,0.000002282273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002356659,"about_ca_system_score_gemma":0.00001314493,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002923579,"about_ca_topic_score_gemma":0.00005210526,"domain_scores_codex":[0.9991465,0.00004269414,0.0003186917,0.0001659826,0.0001057326,0.0002203774],"domain_scores_gemma":[0.9995434,0.0002230397,0.00004608521,0.0001467174,0.00001446453,0.00002633134],"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":[0.00003291544,0.0000544936,0.000005975932,0.0003558752,0.00008513387,0.000006276083,0.001012646,0.9224308,0.02123814,0.008603166,0.000006772427,0.04616786],"study_design_scores_gemma":[0.0004162758,0.00004245047,0.00005320389,0.0005605792,0.00003186884,0.000003722626,0.0001320926,0.8561563,0.1395207,0.002927081,0.00002081798,0.0001348879],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5002369,0.00001363868,0.4988506,0.00001667866,0.0004438839,0.00009596805,0.000003189411,0.00005550223,0.0002836762],"genre_scores_gemma":[0.9936808,0.000009142585,0.006209678,0.00003115002,0.00001785233,0.000004465574,0.000001461002,0.00001602473,0.00002939955],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.493444,"threshold_uncertainty_score":0.5270187,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005935516813452162,"score_gpt":0.2147835631961579,"score_spread":0.2088480463827057,"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."}}