{"id":"W4252582826","doi":"10.32920/ryerson.14656728","title":"Security and collision in RFID systems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"RFID technology advancements","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Radio-frequency identification; Hash function; Authentication (law); Computer security; Identification (biology); Timestamp; Authentication protocol; Computer network; Cryptography; Encryption; Protocol (science)","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":[0.00008321353,0.0001444247,0.0002448606,0.0001202463,0.000009647708,0.0000370962,0.0001121575,0.000371231,0.00001593909],"category_scores_gemma":[0.00001716499,0.0001581403,0.00001544392,0.00009337113,0.00001781944,0.00004754277,0.0003713722,0.0004994319,0.000004722679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001046399,"about_ca_system_score_gemma":0.00001088411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007212271,"about_ca_topic_score_gemma":0.0001421799,"domain_scores_codex":[0.9993394,0.00001427521,0.0001939823,0.0002344291,0.00007787464,0.0001400142],"domain_scores_gemma":[0.9996073,0.00001679526,0.00001901088,0.0003146179,0.00001818317,0.00002408045],"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":[0.00000840665,0.0001167345,0.0530432,0.005531438,0.0002645334,0.0004582135,0.0010994,0.9267755,0.003157841,0.004686993,0.002013368,0.00284443],"study_design_scores_gemma":[0.001761188,0.00003971133,0.01556938,0.002855628,0.00004753881,0.00007008607,0.002356358,0.9400178,0.02029924,0.006700279,0.008621206,0.001661584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9862299,0.00502401,0.002609406,0.00002226885,0.000964703,0.0002901223,0.000008372084,0.0004360805,0.00441512],"genre_scores_gemma":[0.9977574,0.0011732,0.000867178,0.000005439379,0.00001541105,0.00006504369,0.00002142456,0.00001951085,0.00007537011],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03747382,"threshold_uncertainty_score":0.6448773,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00570405400687602,"score_gpt":0.2113442913395484,"score_spread":0.2056402373326724,"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."}}