{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003344381,0.00022179,0.0002845504,0.00005228003,0.0006350655,0.0001124104,0.001061993,0.0002481672,0.000003619634],"category_scores_gemma":[0.00004040041,0.000244252,0.00006304507,0.0006711163,0.0001925961,0.0008183932,0.0008478506,0.0008553659,0.000004841374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001407879,"about_ca_system_score_gemma":0.00005296101,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001028247,"about_ca_topic_score_gemma":0.0002793927,"domain_scores_codex":[0.9978283,0.0004582213,0.0005229169,0.0004215435,0.0002874205,0.0004815677],"domain_scores_gemma":[0.997799,0.0002872167,0.0002201519,0.00143511,0.0001329375,0.0001255278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008108078,0.0008162876,0.01687728,0.00009750314,0.00006313614,0.0000796905,0.1257377,0.02657551,0.000005081936,0.6899918,0.004261475,0.1354135],"study_design_scores_gemma":[0.0006716723,0.0001222183,0.00597658,0.0001937672,0.000005171388,0.0001262305,0.0003742024,0.9545704,0.00004557242,0.02591429,0.01153478,0.0004651504],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5239069,0.03292558,0.4246628,0.01457314,0.00069603,0.001218791,0.00002444378,0.0006768538,0.00131537],"genre_scores_gemma":[0.9804785,0.0123951,0.00596611,0.0008717606,0.00006540943,0.00004435166,0.0001623902,0.00001239373,0.000003938774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9279948,"threshold_uncertainty_score":0.9960309,"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."}}