{"id":"W2088116698","doi":"10.1109/aps.2012.6348003","title":"Ultra-wideband interference modelling for indoor wireless channels using the FDTD method","year":2012,"lang":"en","type":"article","venue":"","topic":"Ultra-Wideband Communications Technology","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Finite-difference time-domain method; Clutter; Wideband; Power delay profile; Exponential decay; Exponential function; Wireless; Ultra-wideband; Interference (communication); Electronic engineering; Delay spread; Acoustics; Computer science; Radio propagation; Power (physics); Computational physics; Fading; Physics; Channel (broadcasting); Telecommunications; Optics; Engineering; Radar; Mathematics; Mathematical analysis","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":[0.0001521582,0.0003543688,0.0003152628,0.0003198269,0.0002037968,0.0003918245,0.0005641268,0.0005892431,0.001185828],"category_scores_gemma":[0.0003767785,0.0002630798,0.0005172581,0.000410054,0.0002177275,0.0004555388,0.0002223029,0.0003742943,0.0004140768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003770627,"about_ca_system_score_gemma":0.000471755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004448344,"about_ca_topic_score_gemma":0.002230435,"domain_scores_codex":[0.999895,0.00002420775,0.000003828027,0.000009966593,0.00004802624,0.00001902866],"domain_scores_gemma":[0.9998666,0.0000530182,0.00001723664,0.0000185967,0.00003838716,0.000006101272],"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":[0.00003123712,0.00002644787,0.0006348398,0.00005971465,0.00001948841,0.0001676743,0.00009888472,0.9560393,0.02006394,0.008179332,0.0005387034,0.01414057],"study_design_scores_gemma":[0.000003566672,0.00001286051,0.0001293236,0.000005331667,0.000004163504,0.00006106805,0.00001007266,0.9965681,0.001465478,0.0005090131,0.001225625,0.000005372833],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03303945,0.0003265485,0.9587281,0.0000721738,0.00004731355,0.0000256445,0.00007956893,0.000378765,0.007302481],"genre_scores_gemma":[0.8004751,0.001319668,0.1870361,0.00006294407,0.00004860212,0.000143803,0.0002200235,0.000139582,0.01055421],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004448344,"threshold_uncertainty_score":0.008844912,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05665433843019693,"score_gpt":0.2939034974226037,"score_spread":0.2372491589924068,"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."}}