{"id":"W3011010717","doi":"10.1186/s12942-020-00201-9","title":"Daily activity locations k-anonymity for the evaluation of disclosure risk of individual GPS datasets","year":2020,"lang":"en","type":"article","venue":"International Journal of Health Geographics","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"General Electric (Canada); University of Toronto","funders":"University of Toronto Mississauga; University of Toronto; National Science Foundation","keywords":"Anonymity; Geospatial analysis; Global Positioning System; Confidentiality; Computer science; Geographic information system; Data mining; Internet privacy; Data science; Geography; Computer security; Remote sensing; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01611453,0.001094876,0.001001811,0.004023661,0.00140123,0.002542508,0.001435884,0.001383859,0.001052226],"category_scores_gemma":[0.06726689,0.0001993693,0.001230811,0.003521025,0.001972003,0.004578891,0.003269881,0.001384007,0.0002195515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002924127,"about_ca_system_score_gemma":0.002329428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002865119,"about_ca_topic_score_gemma":0.002050062,"domain_scores_codex":[0.9762956,0.01240309,0.001994921,0.002121253,0.006204747,0.0009803891],"domain_scores_gemma":[0.9080818,0.05815762,0.01395236,0.01108309,0.007102082,0.001623104],"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":[0.002544194,0.000504329,0.2136524,0.001205056,0.001082503,0.0007252963,0.001539628,0.537168,0.003314664,0.05994486,0.006966913,0.1713522],"study_design_scores_gemma":[0.0000588175,0.0008255639,0.03119982,0.0002127911,0.0002187474,0.00112798,0.001755533,0.9028448,0.005565135,0.05104248,0.004935032,0.000213459],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.677312,0.003538813,0.2995333,0.00179583,0.0003177525,0.0007803093,0.005887776,0.000835845,0.009998452],"genre_scores_gemma":[0.9753591,0.0003156344,0.02277196,0.00006540261,0.00005775317,0.0001649672,0.000921591,0.00001551905,0.0003280829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01611453,"threshold_uncertainty_score":0.08522284,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1170293751477343,"score_gpt":0.3914867637833019,"score_spread":0.2744573886355676,"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."}}