{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01276351,0.001040093,0.001330063,0.001320701,0.002105998,0.009765705,0.002549633,0.004257937,0.002001917],"category_scores_gemma":[0.02655615,0.0007377979,0.001244154,0.001635151,0.00645375,0.01629187,0.00505995,0.005025676,0.00038442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003130355,"about_ca_system_score_gemma":0.002560558,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001507996,"about_ca_topic_score_gemma":0.0007611151,"domain_scores_codex":[0.9865437,0.006855654,0.0008378533,0.001318366,0.003375456,0.001068979],"domain_scores_gemma":[0.9758458,0.01370725,0.002121719,0.005221732,0.002396337,0.0007071666],"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":[0.0002321954,0.0001057015,0.003705225,0.0005702418,0.0001547872,0.0005371646,0.001291832,0.03014909,0.004074563,0.864236,0.004850953,0.09009222],"study_design_scores_gemma":[0.0000704203,0.0002786624,0.001694902,0.0005097909,0.0001276943,0.001306066,0.001013513,0.1619835,0.003704426,0.7885138,0.04071316,0.00008395925],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02186738,0.01108845,0.9088708,0.03975179,0.0005752763,0.0002112264,0.0001455946,0.0002272812,0.01726216],"genre_scores_gemma":[0.8528863,0.009463693,0.129437,0.002788241,0.001611004,0.0002776885,0.0001276554,0.00008643144,0.003321879],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01276351,"threshold_uncertainty_score":0.06750065,"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."}}