{"id":"W4387870379","doi":"10.1109/icc45041.2023.10278950","title":"Reconfigurable Intelligent Surface-induced Randomness for mmWave Key Generation","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Stiftelsen för Strategisk Forskning","keywords":"Randomness; Key generation; Computer science; Channel (broadcasting); Key (lock); Wireless; Multipath propagation; Physical layer; Exploit; Computer network; Electronic engineering; Algorithm; Telecommunications; Cryptography; Engineering; Mathematics; Computer security","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":[0.0002745125,0.0003766113,0.0002694889,0.000268491,0.0002100367,0.000469165,0.0003816865,0.0003832351,0.0009772209],"category_scores_gemma":[0.0007311458,0.0001581362,0.0003399967,0.0002891148,0.0007546016,0.0006873747,0.0005232956,0.0003746824,0.0002509393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004261642,"about_ca_system_score_gemma":0.0001963129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001340162,"about_ca_topic_score_gemma":0.0001393464,"domain_scores_codex":[0.9997316,0.00006565985,0.00001027846,0.00004289691,0.0001058179,0.00004375466],"domain_scores_gemma":[0.9996094,0.0001540666,0.00009561416,0.00007537383,0.00004770013,0.00001797785],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003678476,0.0001088861,0.002152178,0.0002322035,0.00006262511,0.0004342029,0.0001508093,0.3426414,0.3862725,0.2195822,0.0009762757,0.04701906],"study_design_scores_gemma":[0.00002956426,0.0002871352,0.0007523756,0.00001198066,0.0000179158,0.0002274992,0.00003340814,0.9099281,0.06979498,0.01610106,0.002770912,0.00004506017],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2258904,0.0005317947,0.7604088,0.0002914213,0.000103217,0.0000739579,0.0000784453,0.0004198701,0.01220219],"genre_scores_gemma":[0.9689042,0.0001459939,0.02993211,0.00003868461,0.00001842217,0.00003063376,0.00002280062,0.00002383908,0.0008832002],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009772209,"threshold_uncertainty_score":0.003269136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07934600370415383,"score_gpt":0.2874534054501356,"score_spread":0.2081074017459817,"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."}}