{"id":"W1952234003","doi":"10.1002/cpe.3065","title":"RSEL: revocable secure efficient lightweight RFID authentication scheme","year":2013,"lang":"en","type":"article","venue":"Concurrency and Computation Practice and Experience","topic":"RFID technology advancements","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Fundamental Research Funds for the Central Universities; Ministry of Education of the People's Republic of China; National Natural Science Foundation of China; National Science and Technology Major Project; Strong","keywords":"Computer science; Authentication (law); Hash function; Correctness; Radio-frequency identification; Computer security; Key (lock); Scheme (mathematics); Database; Computer network","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":[0.001027094,0.0005020811,0.0006427719,0.0009656763,0.0005707159,0.001087096,0.001215512,0.0009808793,0.004355462],"category_scores_gemma":[0.001953278,0.0002069447,0.0006239304,0.0005996167,0.0008248821,0.002371428,0.002425811,0.0009053356,0.002432274],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007056188,"about_ca_system_score_gemma":0.0008882238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004427382,"about_ca_topic_score_gemma":0.0002861305,"domain_scores_codex":[0.9984471,0.0003673945,0.0001682481,0.0002199792,0.0004987628,0.0002985107],"domain_scores_gemma":[0.9983227,0.0002476042,0.0003266996,0.0006501852,0.0003631216,0.00008971994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004044823,0.0003302309,0.003125985,0.0009219479,0.0002191874,0.002747568,0.0009383312,0.06298594,0.3161404,0.1683085,0.02050297,0.419734],"study_design_scores_gemma":[0.0007371873,0.001694743,0.001907445,0.0001710722,0.0002182514,0.004858755,0.0003242178,0.5499788,0.2545563,0.06110025,0.1240264,0.0004266179],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1619752,0.002057493,0.8060753,0.001145768,0.000523427,0.0006053605,0.0004424303,0.01009751,0.01707754],"genre_scores_gemma":[0.9200009,0.0003769525,0.06537319,0.0002778238,0.00008717671,0.000155249,0.0004260404,0.00009939121,0.01320323],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004355462,"threshold_uncertainty_score":0.01457047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00849781266219176,"score_gpt":0.264465261212887,"score_spread":0.2559674485506953,"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."}}