{"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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.01820426,0.00008244268,0.000296311,0.00008473654,0.0007311263,0.0002171014,0.0005344552,0.00006647159,0.000001972671],"category_scores_gemma":[0.02270733,0.00004365048,0.00007460899,0.0003429667,0.0003142472,0.00200931,0.0001999274,0.0005065766,2.641736e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000551453,"about_ca_system_score_gemma":0.0005395536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001114546,"about_ca_topic_score_gemma":0.001001372,"domain_scores_codex":[0.9961087,0.001417465,0.0008528542,0.00004742915,0.001192698,0.0003809117],"domain_scores_gemma":[0.9860654,0.01145622,0.00169112,0.0001812587,0.0004574242,0.0001485037],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0008579919,0.00144888,0.3421932,0.0002743522,0.000395336,0.000005735911,0.5115778,0.000007833298,0.00001882798,0.005041831,0.06490836,0.0732698],"study_design_scores_gemma":[0.003699291,0.001717199,0.1659447,0.000304417,0.0002322069,0.0001701418,0.7635117,0.03258145,0.00001651411,0.0005496488,0.03098872,0.0002840509],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9706455,0.00001629073,0.003683585,0.02397647,0.0001043188,0.001477867,0.0000788347,0.000003331608,0.00001374024],"genre_scores_gemma":[0.9975172,0.00003800668,0.0009272756,0.001292101,0.0001672161,0.00003405765,0.00001497252,0.000004076538,0.000005129478],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2519338,"threshold_uncertainty_score":0.9855248,"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."}}