{"id":"W2266573070","doi":"","title":"Every step you fake: a comparative analysis of fitness tracker privacy and security","year":2016,"lang":"en","type":"article","venue":"","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Activity tracker; Purchasing; Internet privacy; Wearable computer; BitTorrent tracker; Wearable technology; Business; Computer science; Advertising; Marketing; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006295692,0.00009504666,0.0002976226,0.0001665342,0.0002223101,0.00004263614,0.0002823393,0.00009301154,0.0005461324],"category_scores_gemma":[0.000317326,0.00006489415,0.00007980152,0.0007041206,0.0003799006,0.0005928535,0.0001614824,0.00006273888,0.00001242225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004803977,"about_ca_system_score_gemma":0.00006916824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004638919,"about_ca_topic_score_gemma":0.009524277,"domain_scores_codex":[0.998771,0.0002458384,0.0002164201,0.0002616491,0.0003046615,0.0002005047],"domain_scores_gemma":[0.9991628,0.0001921788,0.0001169559,0.0002896686,0.0001360236,0.0001023607],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005949079,0.001439741,0.3705911,0.0001410972,0.003569919,0.00001032297,0.2737566,0.000004017406,0.004682953,0.2574503,0.02388855,0.06387055],"study_design_scores_gemma":[0.003417952,0.0003556914,0.6942614,0.0001195979,0.002053213,0.00000243035,0.0406296,0.001545947,0.008342874,0.07073779,0.1771497,0.001383733],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9823046,0.0001563527,0.004754123,0.00149623,0.00009688702,0.0002701833,0.000106961,0.0000604522,0.01075421],"genre_scores_gemma":[0.9989251,0.0001747721,0.0002846027,0.00004098696,0.00005746078,0.00001069141,0.000008422388,0.000002526117,0.0004954215],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3236703,"threshold_uncertainty_score":0.7012689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04373893380706582,"score_gpt":0.3341687578573157,"score_spread":0.2904298240502499,"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."}}