{"id":"W4406142049","doi":"10.1137/1.9781611978322.92","title":"Private Mean Estimation with Person-Level Differential Privacy","year":2025,"lang":"en","type":"book-chapter","venue":"Society for Industrial and Applied Mathematics eBooks","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Google (Canada); University of Waterloo","funders":"","keywords":"Differential privacy; Estimation; Differential (mechanical device); Statistics; Computer science; Mathematics; Economics; Physics; Thermodynamics","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":[0.005047088,0.001160944,0.001613249,0.0007368508,0.0007148904,0.003243203,0.002900055,0.002021693,0.002800714],"category_scores_gemma":[0.02321676,0.0007461506,0.001142414,0.002380318,0.002454646,0.007580476,0.004709468,0.003829017,0.001058914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00217181,"about_ca_system_score_gemma":0.001187718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007424035,"about_ca_topic_score_gemma":0.0004900444,"domain_scores_codex":[0.9949456,0.002048537,0.0001558979,0.001131999,0.001309593,0.0004085194],"domain_scores_gemma":[0.987785,0.007807175,0.0007829854,0.002861104,0.0005793133,0.0001844767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003721658,0.0001147489,0.00271492,0.0002678383,0.0001458911,0.0003017564,0.0004083703,0.2307391,0.00523309,0.6139302,0.005830445,0.1399415],"study_design_scores_gemma":[0.00002008635,0.00007811213,0.0004883901,0.0000327509,0.00002998952,0.0003243743,0.00005920103,0.69529,0.004340507,0.2944954,0.004807649,0.00003367715],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004946189,0.0003332683,0.9922622,0.00034769,0.00003115099,0.00002178869,0.00009711898,0.0001088998,0.00185161],"genre_scores_gemma":[0.5418915,0.002222766,0.4417835,0.0007170447,0.000456121,0.0002495043,0.0006312365,0.0001899143,0.01185852],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005047088,"threshold_uncertainty_score":0.02669185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09075183347604178,"score_gpt":0.2588734497257937,"score_spread":0.168121616249752,"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."}}