{"id":"W2809372353","doi":"10.1109/tits.2018.2841402","title":"Simulation of the Bluetooth Inquiry Process for Application in Transportation Engineering","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Bluetooth and Wireless Communication Technologies","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Bluetooth; Detector; Process (computing); Microsimulation; Computer science; Simulation software; Intelligent transportation system; Simulation; Real-time computing; Software; Engineering; Wireless; Telecommunications; Transport engineering; Operating system","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":[0.0006150675,0.0005325467,0.0005645423,0.0005665136,0.0005397373,0.0006800872,0.0009012149,0.001120713,0.003896725],"category_scores_gemma":[0.001839852,0.0002969033,0.0006602036,0.0005050814,0.0004253691,0.0005875864,0.0006355873,0.0007235201,0.0002883886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007986188,"about_ca_system_score_gemma":0.001241233,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01412143,"about_ca_topic_score_gemma":0.007054437,"domain_scores_codex":[0.999752,0.00008716315,0.00001386919,0.0000335568,0.00006430441,0.0000491255],"domain_scores_gemma":[0.9990012,0.0006546138,0.00006774473,0.00005918676,0.0001679621,0.00004927327],"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":[0.0000196993,0.00002993746,0.0007273672,0.00001442584,0.000004622664,0.00002303265,0.00002658207,0.9949554,0.0005228569,0.002094125,0.0001166839,0.001465374],"study_design_scores_gemma":[0.000004800752,0.00001348329,0.0001094159,0.000002789318,0.000002330207,0.000004176188,0.000008042301,0.9989512,0.0002504856,0.0003434513,0.0003069588,0.000002935338],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4410049,0.0003862821,0.52558,0.0005492559,0.000145129,0.0003699452,0.001014418,0.001325325,0.02962481],"genre_scores_gemma":[0.9561586,0.000245051,0.03894661,0.00003973504,0.00001267678,0.0003254538,0.0003733757,0.00005134364,0.003847196],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01412143,"threshold_uncertainty_score":0.0280785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04102815298991618,"score_gpt":0.2953207211547129,"score_spread":0.2542925681647967,"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."}}