{"id":"W2324889137","doi":"10.4236/jcc.2014.27003","title":"Scalable Trust-Based Secure WSNs","year":2014,"lang":"en","type":"article","venue":"Journal of Computer and Communications","topic":"Security in Wireless Sensor Networks","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Scalability; Computer science; Wireless sensor network; Trust management (information system); Cryptography; Computer network; Key management; Computation; Focus (optics); Key (lock); Distributed computing; Key distribution in wireless sensor networks; Public-key cryptography; Cryptographic protocol; Wireless; Wireless network; Computer security; Encryption; Algorithm; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001478747,0.0005551949,0.0008031115,0.0005326678,0.00073377,0.0009987131,0.001194975,0.0005322369,0.001456233],"category_scores_gemma":[0.00355361,0.000317616,0.000570985,0.0008100754,0.0009401875,0.003026256,0.002482873,0.0008247006,0.0004108668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000904901,"about_ca_system_score_gemma":0.0007384018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009160357,"about_ca_topic_score_gemma":0.0009810429,"domain_scores_codex":[0.9984661,0.0003399483,0.0001377246,0.0002913828,0.0006197243,0.0001450359],"domain_scores_gemma":[0.9982626,0.0005629156,0.0002532527,0.0004263333,0.0003608032,0.0001340857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005330073,0.0001485083,0.002265718,0.0004692665,0.0002303586,0.001285827,0.0005972299,0.575727,0.0441561,0.2296228,0.005257494,0.1397067],"study_design_scores_gemma":[0.00004666887,0.0001350721,0.0003916406,0.00002408531,0.00004620436,0.0001744403,0.00007660372,0.9255555,0.005736095,0.06281088,0.004979696,0.00002311716],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04969169,0.0007624454,0.9429921,0.0006159853,0.000144896,0.0001680853,0.0001057633,0.0009445535,0.004574395],"genre_scores_gemma":[0.9060767,0.0005750307,0.09009261,0.0000856156,0.00007434257,0.0001669664,0.0001405604,0.0000570337,0.00273105],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001478747,"threshold_uncertainty_score":0.007820427,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0142212776788967,"score_gpt":0.2462944970272543,"score_spread":0.2320732193483576,"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."}}