{"id":"W2131093212","doi":"10.1109/glocom.2010.5683999","title":"Time Correlation Analysis of Secret Key Generation via UWB Channels","year":2010,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Key (lock); Computer science; Key generation; Channel (broadcasting); Spatial correlation; Secrecy; Wireless; Characterization (materials science); Algorithm; Cryptography; Computer network; Telecommunications; Computer security; Physics","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":[0.0001570992,0.00007298366,0.0001514938,0.0002725766,0.00002426935,0.00001485996,0.0001472399,0.0001066772,0.0007888054],"category_scores_gemma":[0.00001475443,0.00007728628,0.00006266506,0.0004403809,0.0000240553,0.0001420029,0.00002375627,0.000137698,0.00003886304],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000141928,"about_ca_system_score_gemma":0.000004023005,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003858255,"about_ca_topic_score_gemma":0.0001343925,"domain_scores_codex":[0.9995114,0.00001895637,0.0002147748,0.00007626776,0.0001066598,0.00007198005],"domain_scores_gemma":[0.9993864,0.00003252991,0.00004277282,0.0004283458,0.00008166798,0.00002828729],"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":[0.000001437812,0.00002739715,0.0006788276,0.000009099075,0.0002843495,1.396901e-7,0.0007981416,0.0932032,0.8950661,0.004631234,0.001447212,0.003852831],"study_design_scores_gemma":[0.00003280693,0.000005428947,0.0008948905,0.000001385902,0.00007053289,3.354539e-7,0.000004131664,0.9065355,0.09151811,0.00007927808,0.0007820852,0.00007553001],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6789815,0.00002317246,0.3132704,0.00005000266,0.0001078316,0.0001031066,0.000006357779,0.0005490492,0.006908591],"genre_scores_gemma":[0.9900671,0.00001768083,0.009454942,0.00001618416,0.00003602526,0.00001277491,0.0002132404,0.00001332351,0.0001687588],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8133323,"threshold_uncertainty_score":0.8636867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009888231358007609,"score_gpt":0.2261635257363186,"score_spread":0.216275294378311,"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."}}