{"id":"W87086807","doi":"10.1007/978-3-642-23041-7_23","title":"Mobile Agent Code Updating and Authentication Protocol for Code-Centric RFID System","year":2011,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"RFID technology advancements","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Authentication (law); Code (set theory); Mobile agent; Authentication protocol; Protocol (science); Tracing; Identification (biology); Computer security; Embedded system; Computer network; Operating system; Programming language","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":[0.0007790011,0.0004946277,0.0005934821,0.0007601905,0.00093825,0.001474618,0.001282395,0.001145212,0.002625592],"category_scores_gemma":[0.001921105,0.0003185913,0.0002969798,0.0006611566,0.0004664884,0.001967671,0.001510563,0.001526679,0.001818207],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005139736,"about_ca_system_score_gemma":0.001129788,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007364763,"about_ca_topic_score_gemma":0.0006498549,"domain_scores_codex":[0.9990917,0.0001734907,0.00009317567,0.000148173,0.0003512075,0.0001421922],"domain_scores_gemma":[0.9985489,0.0001910565,0.000157445,0.0004060861,0.0006111867,0.00008532443],"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":[0.001871232,0.0004518953,0.002035097,0.0007140966,0.0001258014,0.001574775,0.001325951,0.01969552,0.2004381,0.1479445,0.04542647,0.5783966],"study_design_scores_gemma":[0.0002723896,0.001139847,0.001885836,0.0001643394,0.0002902219,0.004694051,0.000306543,0.448215,0.3258477,0.03056179,0.1863583,0.0002638056],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0499907,0.001818734,0.9157842,0.0005305033,0.0008205986,0.0006410297,0.0002303805,0.008067219,0.02211668],"genre_scores_gemma":[0.7474467,0.001258621,0.2026332,0.0003745964,0.0003633099,0.0007656633,0.0007800851,0.0003191786,0.04605868],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002625592,"threshold_uncertainty_score":0.00878346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02014622637499134,"score_gpt":0.2628901510342149,"score_spread":0.2427439246592236,"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."}}