{"id":"W1986199471","doi":"10.1016/j.adhoc.2010.07.007","title":"Computationally efficient mutual entity authentication in wireless sensor networks","year":2010,"lang":"en","type":"article","venue":"Ad Hoc Networks","topic":"Security in Wireless Sensor Networks","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mutual authentication; Wireless sensor network; Computer science; Computer network; Authentication (law); Computer security","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008472175,0.0003886383,0.0004112039,0.0002335459,0.0002613934,0.0003908782,0.001445038,0.0004613867,0.0000385479],"category_scores_gemma":[0.0000611145,0.0004235371,0.000149971,0.001226795,0.0002149203,0.0003687111,0.0004360797,0.001451352,0.00010181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001062762,"about_ca_system_score_gemma":0.0000862947,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002498129,"about_ca_topic_score_gemma":0.0004234935,"domain_scores_codex":[0.9965428,0.000235395,0.0007158005,0.0009440328,0.0006161759,0.0009457582],"domain_scores_gemma":[0.9973756,0.0006836265,0.0002952525,0.001116175,0.0002644356,0.0002649271],"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":[0.00002513258,0.0002740735,0.001950042,0.000008084224,0.00002546239,0.00004793429,0.0006921923,0.9274969,0.0002057913,0.03672674,0.0004581721,0.03208948],"study_design_scores_gemma":[0.0006427153,0.00004122623,0.03399697,0.00004632931,0.0000114104,0.00004111041,0.00002541951,0.9633756,0.00002765117,0.0005258232,0.000823916,0.0004417829],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5593386,0.000274426,0.4371269,0.0004281979,0.001954118,0.0003631002,0.000001764797,0.0002867455,0.0002260981],"genre_scores_gemma":[0.9857322,0.0001139679,0.01288053,0.0004899162,0.0005699454,0.00004240501,0.00005599474,0.00004110003,0.00007395852],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4263935,"threshold_uncertainty_score":0.9998217,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006386125073379109,"score_gpt":0.2266709837802555,"score_spread":0.2202848587068764,"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."}}