{"id":"W2157837881","doi":"10.1109/issse.2007.4294530","title":"On the TOA Estimation for UWB Ranging in Complex Confined Area","year":2007,"lang":"en","type":"article","venue":"","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Ranging; Time of arrival; Computer science; Multipath propagation; Real-time computing; SIGNAL (programming language); Channel (broadcasting); Algorithm; Direction of arrival; Wireless; Sensitivity (control systems); Electronic engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001863233,0.000060698,0.00006378971,0.00009258949,0.00003755849,0.00001415216,0.00007194769,0.0000458994,0.0001069372],"category_scores_gemma":[0.000103661,0.00004255965,0.00002025958,0.0001351505,0.00001524745,0.00002655176,0.000005620322,0.0000495795,0.0000113011],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003267129,"about_ca_system_score_gemma":0.000002159481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007035457,"about_ca_topic_score_gemma":0.00005372552,"domain_scores_codex":[0.9996303,0.00000254072,0.0001218104,0.00005370891,0.0000505818,0.0001410431],"domain_scores_gemma":[0.9996715,0.0002019236,0.000009307243,0.00009375872,0.00001540123,0.000008167109],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003113712,0.00001673082,0.0002276306,0.0000431517,0.00001359946,0.000002057028,0.0004402622,0.373525,0.003039278,0.5772222,0.01188406,0.03355488],"study_design_scores_gemma":[0.0003270432,0.00001533167,0.0008956118,0.00001115216,0.000001890654,5.904183e-7,0.000253911,0.954482,0.03566089,0.006813778,0.00145664,0.00008113545],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04914999,0.000008210284,0.9321236,0.0003128647,0.00006525053,0.0002414129,0.000001925836,0.0004687071,0.01762805],"genre_scores_gemma":[0.9967962,0.000001429233,0.002880242,0.0001843931,0.000008559366,0.00001594465,0.00001301312,0.0000092477,0.00009100851],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9476462,"threshold_uncertainty_score":0.1735532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0260085003608562,"score_gpt":0.2437456374276815,"score_spread":0.2177371370668253,"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."}}