{"id":"W2807229072","doi":"10.1016/j.pmcj.2018.05.006","title":"Traffic characterization and LTE performance analysis for M2M communications in smart cities","year":2018,"lang":"en","type":"article","venue":"Pervasive and Mobile Computing","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":37,"is_retracted":false,"has_abstract":false,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"EnodeB; Computer science; Context (archaeology); Network packet; Smart city; Machine to machine; Throughput; Computer network; Wireless; Real-time computing; Telecommunications; User equipment; Internet of Things; Computer security; Base station","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":[0.0006433041,0.0006666848,0.0003783305,0.00204302,0.0006942317,0.0009122182,0.0004352338,0.0006191304,0.0007809845],"category_scores_gemma":[0.002338242,0.0002434897,0.0003717221,0.001636175,0.0003483735,0.0008838743,0.0003065416,0.0002842642,0.00026575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001292406,"about_ca_system_score_gemma":0.000565322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01786736,"about_ca_topic_score_gemma":0.01249988,"domain_scores_codex":[0.9995059,0.0001164764,0.00002650008,0.00005921649,0.0001396193,0.0001522951],"domain_scores_gemma":[0.9990705,0.0003707436,0.00008955471,0.00009971941,0.0003342819,0.0000352559],"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":[0.0008416033,0.0002113825,0.05163268,0.000116548,0.00008705527,0.0004645523,0.0003020174,0.8331333,0.04585947,0.007592358,0.002231759,0.05752731],"study_design_scores_gemma":[0.000004610514,0.00007787823,0.01516034,0.000005650494,0.00002036498,0.0001269587,0.0001371028,0.9756576,0.007168389,0.00108759,0.0005359892,0.00001752437],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9281189,0.0002888269,0.06672505,0.0001293433,0.00002069576,0.00003981129,0.0004816852,0.0006413964,0.003554307],"genre_scores_gemma":[0.9972832,0.0000595694,0.001868311,0.00001093026,0.000008066033,0.000009243776,0.0003289034,0.0000215412,0.0004101295],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01786736,"threshold_uncertainty_score":0.03552669,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01542545791145965,"score_gpt":0.2378908742863176,"score_spread":0.2224654163748579,"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."}}