{"id":"W2100509127","doi":"10.1002/sec.40","title":"Enforcing patient privacy in healthcare WSNs through key distribution algorithms","year":2008,"lang":"en","type":"article","venue":"Security and Communication Networks","topic":"Security in Wireless Sensor Networks","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Division of Electrical, Communications and Cyber Systems","keywords":"Computer science; Cryptography; Elliptic curve cryptography; Key (lock); Session key; Computer security; Key distribution; Key generation; Computer network; Wireless sensor network; Algorithm; Public-key cryptography; Encryption","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":[0.005059926,0.0004493566,0.0006288047,0.0005779576,0.0006303873,0.001385312,0.001081273,0.0009417219,0.001208123],"category_scores_gemma":[0.008414596,0.000261276,0.0003287839,0.00068392,0.001486971,0.002784573,0.00217567,0.0008692945,0.00049182],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007344098,"about_ca_system_score_gemma":0.0009677841,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000287344,"about_ca_topic_score_gemma":0.0001762957,"domain_scores_codex":[0.996869,0.001783786,0.000237151,0.0003112229,0.0006225833,0.0001762404],"domain_scores_gemma":[0.9934576,0.003559937,0.0008912619,0.001335149,0.0006068602,0.0001491213],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001902278,0.0004473232,0.007434286,0.0004153228,0.0001534919,0.0007364331,0.001154375,0.3467006,0.08304266,0.1840883,0.004488695,0.3694361],"study_design_scores_gemma":[0.0002101755,0.0002515827,0.0007312555,0.00004423846,0.00004285641,0.000593073,0.0001642876,0.8711331,0.0502483,0.0691913,0.007348682,0.00004112406],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04275066,0.000233611,0.9545811,0.0004396446,0.00003281916,0.00009219227,0.00002669905,0.0004442536,0.001398938],"genre_scores_gemma":[0.7420203,0.0003186897,0.2557328,0.0001269474,0.0000440502,0.0001455753,0.00006629337,0.00005608337,0.001489153],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005059926,"threshold_uncertainty_score":0.0267598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01907875676628015,"score_gpt":0.2469031627615002,"score_spread":0.22782440599522,"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."}}