{"id":"W2162881374","doi":"10.1136/amiajnl-2012-001011","title":"Privacy by Design at Population Data BC: a case study describing the technical, administrative, and physical controls for privacy-sensitive secondary use of personal information for research in the public interest","year":2012,"lang":"en","type":"article","venue":"Journal of the American Medical Informatics Association","topic":"Health disparities and outcomes","field":"Social Sciences","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Internet privacy; Information privacy; Privacy policy; Due diligence; Population; Privacy by Design; Privacy law; Computer security; Computer science; Business; Public relations; Environmental health; Medicine; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","open_science"],"consensus_categories":[],"category_scores_codex":[0.04284012,0.0008869126,0.0007689569,0.002294949,0.02305864,0.0083662,0.003263561,0.009163698,0.002818871],"category_scores_gemma":[0.05573687,0.001057502,0.001370688,0.003140569,0.01678794,0.00679872,0.009565709,0.007765362,0.0004813826],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01404918,"about_ca_system_score_gemma":0.01795269,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02999651,"about_ca_topic_score_gemma":0.0456957,"domain_scores_codex":[0.923812,0.06077618,0.001708748,0.002517469,0.006855235,0.004330508],"domain_scores_gemma":[0.9513617,0.03456442,0.003631184,0.004494799,0.002645658,0.003302273],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001957809,0.001359714,0.03545663,0.0005268087,0.0000811885,0.04685793,0.6905082,0.001681292,0.002413332,0.1555484,0.01215651,0.05321414],"study_design_scores_gemma":[0.0001184119,0.0009948902,0.01176017,0.001557892,0.0001429049,0.04746272,0.6048962,0.005702217,0.006673539,0.04061747,0.2798541,0.0002195376],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7763766,0.001921095,0.08939043,0.05368075,0.0003087951,0.00176399,0.0002983974,0.0001719286,0.07608806],"genre_scores_gemma":[0.9418274,0.001544518,0.03850624,0.005454599,0.00007557387,0.0009673128,0.000089345,0.0001104079,0.01142458],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9967365,"threshold_uncertainty_score":0.2265629,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4037476461701621,"score_gpt":0.4772901401040093,"score_spread":0.07354249393384721,"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."}}