{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01749139,0.0001868182,0.0004436871,0.003613774,0.002458319,0.00322285,0.0007722696,0.0009451178,0.007094762],"category_scores_gemma":[0.0935539,0.0002261951,0.0008809587,0.002936994,0.002914858,0.005430576,0.002570844,0.00140506,0.0005817719],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003185305,"about_ca_system_score_gemma":0.002237763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01467303,"about_ca_topic_score_gemma":0.02237727,"domain_scores_codex":[0.9879936,0.006144161,0.0008839637,0.000744746,0.003369059,0.0008645118],"domain_scores_gemma":[0.8805598,0.07877015,0.017684,0.003725363,0.01638897,0.002871633],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001181274,0.000451866,0.8757853,0.0006300213,0.0003464115,0.0003869073,0.06422085,0.000128799,0.0004039909,0.004790105,0.002771087,0.04890336],"study_design_scores_gemma":[0.00002893561,0.0007618716,0.8590485,0.0004250346,0.0002057625,0.000504924,0.132021,0.0007668943,0.0002189297,0.0005451564,0.00543007,0.00004276912],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9849358,0.001010161,0.0005090253,0.0009445125,0.00003373539,0.0001476492,0.0002911613,0.000007969343,0.0121201],"genre_scores_gemma":[0.9982988,0.0003525108,0.0002489577,0.0001216547,0.00001413071,0.00003996107,0.0001439818,0.000006092914,0.0007739574],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01749139,"threshold_uncertainty_score":0.09250438,"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."}}