{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001565556,0.0001061453,0.0001426865,0.00008572375,0.00007928426,0.00002697739,0.0002148079,0.00009017204,0.00004873442],"category_scores_gemma":[0.0000906537,0.000103353,0.00004324541,0.0002887547,0.0000138618,0.0001219665,0.00002461931,0.00009112423,0.0001515997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000563051,"about_ca_system_score_gemma":0.000007503387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005198904,"about_ca_topic_score_gemma":0.00002994922,"domain_scores_codex":[0.9994016,0.00001117498,0.0002068055,0.0001230282,0.00006309211,0.0001942835],"domain_scores_gemma":[0.9993351,0.0001464574,0.00002292981,0.0004124469,0.00005986145,0.00002326865],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000009868969,0.00000783757,0.00001116753,0.00003742027,0.00003285168,4.281655e-7,0.0001564148,0.5636855,0.3429827,0.007092509,0.006553033,0.07943027],"study_design_scores_gemma":[0.000274898,0.00001035571,0.000007911044,0.000005647408,0.000001919872,4.11281e-7,0.0002115692,0.3791128,0.6124268,0.001123798,0.006717532,0.0001063545],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3982012,0.0002471541,0.5879691,0.000556244,0.0005607771,0.0007329139,0.000009602741,0.00586174,0.005861194],"genre_scores_gemma":[0.988983,0.0007751053,0.008914719,0.00001589222,0.00002761978,0.0001695284,0.00006667473,0.00003544674,0.001012004],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5907818,"threshold_uncertainty_score":0.4214614,"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."}}