{"id":"W2998047232","doi":"10.1109/icccnt45670.2019.8944800","title":"Learning Automata Based Secure Multi Agent RFID Authentication System","year":2019,"lang":"en","type":"article","venue":"","topic":"RFID technology advancements","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Authentication (law); Radio-frequency identification; Identification (biology); Learning automata; Computer security; Automaton; Function (biology); Wireless; Server; Protocol (science); Computer network; Artificial intelligence; Operating system","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":[0.0004816243,0.0004239941,0.0005237946,0.00037697,0.001004559,0.001350764,0.001101686,0.0009611245,0.004504825],"category_scores_gemma":[0.001485088,0.0001991748,0.0004970308,0.0002369717,0.0008429254,0.001146525,0.001204162,0.0007163137,0.001064044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008744202,"about_ca_system_score_gemma":0.001213561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002511571,"about_ca_topic_score_gemma":0.002001663,"domain_scores_codex":[0.9990566,0.0001754821,0.0001203723,0.0002705222,0.0002475196,0.0001294454],"domain_scores_gemma":[0.9991049,0.0002716548,0.0001624126,0.0001695073,0.000225729,0.00006575538],"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":[0.00138396,0.0005325762,0.005931214,0.0005625327,0.0001767304,0.003171379,0.001088734,0.5795825,0.07997711,0.1517109,0.007118985,0.1687634],"study_design_scores_gemma":[0.00006356273,0.0001442514,0.0002999362,0.00001845751,0.00003719466,0.0002722846,0.00004026334,0.9687375,0.01275981,0.01350726,0.004092951,0.00002645129],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07844593,0.0002117636,0.9000815,0.000571173,0.0001350103,0.0003094196,0.0001971243,0.00666766,0.01338054],"genre_scores_gemma":[0.9525859,0.0000933324,0.04051535,0.0001081199,0.00001929091,0.0001978951,0.0001082731,0.00003231602,0.006339571],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004504825,"threshold_uncertainty_score":0.01507014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005495276082584044,"score_gpt":0.2028728858528536,"score_spread":0.1973776097702696,"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."}}