{"id":"W1971454239","doi":"10.1049/iet-com.2012.0265","title":"Range‐based localisation and tracking in non‐line‐of‐sight wireless channels with Gaussian scatterer distribution model","year":2013,"lang":"en","type":"article","venue":"IET Communications","topic":"Indoor and Outdoor Localization Technologies","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University; University of Toronto","funders":"","keywords":"Line-of-sight; Range (aeronautics); Gaussian; Non-line-of-sight propagation; Tracking (education); Computer science; Wireless; Distribution (mathematics); Mathematics; Telecommunications; Physics; Mathematical analysis; Engineering; Aerospace 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":[0.00007951979,0.0001056653,0.0001361128,0.0001091642,0.0000774436,0.00003631867,0.0002650294,0.00009332035,0.00001434083],"category_scores_gemma":[0.00001268677,0.00009671337,0.0000183226,0.0002975489,0.0001437191,0.0002116316,0.0000410811,0.0001525794,0.00000672889],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004820696,"about_ca_system_score_gemma":0.00001410559,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009421281,"about_ca_topic_score_gemma":0.0001325508,"domain_scores_codex":[0.9994456,0.00002456204,0.0002250294,0.00009214197,0.00007995451,0.0001326749],"domain_scores_gemma":[0.9992114,0.00005244946,0.0000457962,0.0005773338,0.00008710854,0.00002595954],"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":[0.00001672346,0.0001929031,0.01117135,0.0002547,0.00004297611,8.665799e-7,0.002339517,0.9457143,0.006553805,0.009435064,0.000569094,0.0237087],"study_design_scores_gemma":[0.0003773635,0.00001471013,0.003571535,0.0001140374,0.000007876094,0.000001024062,0.0002148164,0.9832167,0.01176574,0.0005438974,0.0000494983,0.0001227684],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3888192,0.0002126541,0.6089146,0.001100843,0.00001927705,0.0003430359,0.00003081934,0.0002024089,0.0003571444],"genre_scores_gemma":[0.9970129,0.0001511542,0.002417981,0.00003036308,0.000005487617,0.0001858836,0.0001713048,0.00001782322,0.000007136968],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6081936,"threshold_uncertainty_score":0.3943857,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01993510963664299,"score_gpt":0.238712100562452,"score_spread":0.218776990925809,"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."}}