{"id":"W4413775269","doi":"10.1007/s43681-025-00819-0","title":"An assessment of synthetic data generation, use and disclosure under Canadian privacy regulations","year":2025,"lang":"en","type":"article","venue":"AI and Ethics","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Imperial Bank of Commerce (Canada); Children's Hospital of Eastern Ontario; University of Ottawa","funders":"Office of the Privacy Commissioner of Canada; Canadian Institutes of Health Research; Deutsche Forschungsgemeinschaft","keywords":"Internet privacy; Business; Information privacy; Data retention; Accounting; Computer security; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["open_science"],"consensus_categories":[],"category_scores_codex":[0.0006423485,0.00007030845,0.00008696994,0.0001194762,0.000238592,0.0002819421,0.005181421,0.0001562819,0.000002287598],"category_scores_gemma":[0.005525836,0.00006574272,0.000005700494,0.0002340225,0.0001601227,0.001120057,0.01226354,0.0003170712,1.697779e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000286442,"about_ca_system_score_gemma":0.0005525927,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.007295196,"about_ca_topic_score_gemma":0.03544072,"domain_scores_codex":[0.999136,0.00009533353,0.0001408147,0.0003674512,0.0001319325,0.0001284864],"domain_scores_gemma":[0.9932814,0.0002425295,0.00003768441,0.006264906,0.0001104812,0.00006299125],"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":[8.357422e-7,0.00005738717,0.04989227,0.0000829363,0.0000610901,0.000004073609,0.0004930544,0.0001495009,0.0008730923,0.8418493,0.0927313,0.01380515],"study_design_scores_gemma":[0.0000800807,0.00001843016,0.07949977,0.00004294116,0.00001466157,0.000002978061,0.00002995569,0.6972425,0.0001724019,0.2205403,0.002261308,0.000094729],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04936844,0.0001392637,0.6896695,0.2602232,0.0001457525,0.0001206385,0.000119182,0.00008927124,0.0001247485],"genre_scores_gemma":[0.8531049,0.0001542096,0.1456949,0.0009330208,0.000008252743,0.000002530023,0.00007865763,0.00000297077,0.00002058525],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8037364,"threshold_uncertainty_score":0.9993153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1386354598490306,"score_gpt":0.4011649542899396,"score_spread":0.262529494440909,"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."}}