{"id":"W1968064480","doi":"10.1145/2031331.2031336","title":"Trajectory anonymity in publishing personal mobility data","year":2011,"lang":"en","type":"article","venue":"ACM SIGKDD Explorations Newsletter","topic":"Human Mobility and Location-Based Analysis","field":"Social Sciences","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Data publishing; Identifier; Anonymity; Global Positioning System; TRACE (psycholinguistics); Location-based service; Computer security; Object (grammar); World Wide Web; GSM; Mobile device; Location data; Personally identifiable information; k-anonymity; Internet privacy; Data science; Publishing; Computer network; Telecommunications","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":[0.01821933,0.0006490466,0.001833009,0.003221767,0.00388941,0.008955074,0.003697078,0.002358919,0.002228262],"category_scores_gemma":[0.06870109,0.0009008547,0.001336283,0.009061621,0.003936021,0.02051424,0.008629141,0.003220022,0.001555885],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002392814,"about_ca_system_score_gemma":0.003512637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001328973,"about_ca_topic_score_gemma":0.0007051249,"domain_scores_codex":[0.9710475,0.01363624,0.003250269,0.0023148,0.008446764,0.001304571],"domain_scores_gemma":[0.8948246,0.0371167,0.007809563,0.05078919,0.008062039,0.001397982],"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":[0.001022019,0.0001999134,0.01163599,0.0008084534,0.0002132504,0.0008957203,0.00493176,0.04349284,0.006287502,0.6039342,0.01092174,0.3156567],"study_design_scores_gemma":[0.0001293124,0.0004723945,0.002919971,0.0004853025,0.0002875659,0.003940495,0.003851346,0.2416645,0.04948181,0.556316,0.1401921,0.0002593622],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0414396,0.002766902,0.9369996,0.003923298,0.0004612191,0.0002825004,0.0009068308,0.001275149,0.01194487],"genre_scores_gemma":[0.7040697,0.005570541,0.2755642,0.000849315,0.001211254,0.0005882494,0.001696071,0.0003486509,0.01010201],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01821933,"threshold_uncertainty_score":0.09635413,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2671506687550872,"score_gpt":0.3419145920846799,"score_spread":0.07476392332959275,"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."}}