{"id":"W1965740537","doi":"10.1007/s13177-014-0092-1","title":"Bluetooth in Intelligent Transportation Systems: A Survey","year":2014,"lang":"en","type":"article","venue":"International Journal of Intelligent Transportation Systems Research","topic":"Bluetooth and Wireless Communication Technologies","field":"Computer Science","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bluetooth; Leverage (statistics); Electronics; Intelligent transportation system; Dedicated short-range communications; Computer science; Mobile device; Embedded system; Telecommunications; Engineering; Wireless; Electrical engineering; Transport engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.007832648,0.0002485438,0.0005139146,0.002171982,0.0001057265,0.0005465604,0.003923638,0.0002287057,0.00001875346],"category_scores_gemma":[0.0005585467,0.0002240428,0.0001807184,0.001326989,0.0001603249,0.001038397,0.00003478846,0.0009582111,0.00005359238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003867341,"about_ca_system_score_gemma":0.0003194675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002246412,"about_ca_topic_score_gemma":0.001663513,"domain_scores_codex":[0.9931312,0.001186618,0.002254965,0.0004146877,0.002541302,0.0004712307],"domain_scores_gemma":[0.9928159,0.001251854,0.0007825277,0.0006722874,0.004285797,0.000191603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0007635133,0.001504442,0.162248,0.0003958302,0.0006566552,0.000332165,0.01298619,0.1264352,0.001636548,0.5828946,0.003296896,0.1068498],"study_design_scores_gemma":[0.005652368,0.002515875,0.5562342,0.005401816,0.00005613888,0.0002758586,0.01697488,0.2049759,0.02779255,0.01189496,0.1659209,0.002304611],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2122561,0.002057322,0.7805825,0.001322131,0.002699236,0.0005787064,0.00005641461,0.0001125093,0.0003350661],"genre_scores_gemma":[0.9966242,0.001607341,0.001275115,0.00003737067,0.0001459657,0.00005769718,0.00008793853,0.00002443614,0.0001399156],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7843681,"threshold_uncertainty_score":0.9136202,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1067254540656104,"score_gpt":0.3749249746626325,"score_spread":0.2681995205970221,"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."}}