{"id":"W2151850978","doi":"10.1109/twc.2009.080087","title":"A packet-level model for UWB channel with people shadowing process based on angular spectrum analysis","year":2009,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Ultra-Wideband Communications Technology","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Network packet; Ultra-wideband; Channel (broadcasting); Wireless; Power delay profile; Transmission (telecommunications); Real-time computing; Computer network; Bandwidth (computing); Quality of service; Fading; Electronic engineering; Delay spread; Telecommunications; Engineering","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":[0.0008301764,0.0009831027,0.001032381,0.0007142258,0.0005367518,0.001408664,0.002163696,0.001797921,0.003417162],"category_scores_gemma":[0.001943629,0.0005828214,0.0009580831,0.001161171,0.001166499,0.001763905,0.0008290641,0.001721537,0.001069403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001186875,"about_ca_system_score_gemma":0.0008903311,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00829243,"about_ca_topic_score_gemma":0.003658593,"domain_scores_codex":[0.9992982,0.0001655562,0.00003409662,0.0001387057,0.000226045,0.0001372934],"domain_scores_gemma":[0.9989274,0.000542683,0.0001726852,0.00008106766,0.0002365603,0.00003956099],"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":[0.0000488293,0.00003864197,0.0005961587,0.00006702974,0.00002205921,0.0002517625,0.0001323669,0.9336108,0.002528879,0.0577375,0.000631068,0.004334876],"study_design_scores_gemma":[0.000006763697,0.00001690243,0.000103473,0.000004091282,0.00001095986,0.00004740969,0.00001227397,0.9955973,0.0002064575,0.003610642,0.0003750544,0.000008694901],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02287721,0.0004771047,0.969557,0.0003684973,0.00009641093,0.00008249375,0.0004080692,0.0003437128,0.0057894],"genre_scores_gemma":[0.8901455,0.00285245,0.08396296,0.0003250575,0.0002739287,0.0005644917,0.0006407482,0.0001666093,0.02106823],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00829243,"threshold_uncertainty_score":0.01648831,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02447939788259103,"score_gpt":0.2529524657854187,"score_spread":0.2284730679028277,"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."}}