{"id":"W1896093329","doi":"10.1109/mwc.2015.7224734","title":"Security and privacy for mobile healthcare networks: from a quality of protection perspective","year":2015,"lang":"en","type":"article","venue":"IEEE Wireless Communications","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":159,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Computer security; Internet privacy; Information privacy; Perspective (graphical); Wearable computer; Flourishing; Privacy by Design; Wearable technology; Information security","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":"codex-gemma-dda1882f352a","candidate_categories":["open_science"],"consensus_categories":["open_science"],"category_scores_codex":[0.0007271901,0.0001190204,0.0002471197,0.00007611243,0.0002122644,0.00006420299,0.0146015,0.0001346595,3.419749e-7],"category_scores_gemma":[0.003535179,0.0001249399,0.00004582947,0.000388244,0.0002868681,0.0004727659,0.0208433,0.0003097196,0.000001130985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001806465,"about_ca_system_score_gemma":0.0001353939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003741116,"about_ca_topic_score_gemma":0.0005851559,"domain_scores_codex":[0.9985858,0.000344908,0.0003460475,0.0003609156,0.0001729669,0.0001893408],"domain_scores_gemma":[0.9867285,0.0005062597,0.000290914,0.01184837,0.0005434443,0.00008244041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0004103419,0.003368757,0.01563104,0.0005466156,0.0006601666,0.000002117903,0.05581255,0.0008755574,0.005996916,0.6331886,0.04242721,0.2410801],"study_design_scores_gemma":[0.0005069937,0.0001328893,0.0009860134,0.00005818471,0.000007354371,0.000001758136,0.001664086,0.4854552,0.001096215,0.5092149,0.0006999203,0.0001765039],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1790265,0.00283478,0.7848708,0.03083679,0.0001960215,0.001421689,0.0001948061,0.0005372418,0.00008140671],"genre_scores_gemma":[0.8612511,0.0003164274,0.1377614,0.00004359812,0.00002175651,0.0005719133,0.00002339432,0.000008699393,0.000001715586],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6822246,"threshold_uncertainty_score":0.99073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1382238923942548,"score_gpt":0.3783583661921794,"score_spread":0.2401344737979246,"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."}}