{"id":"W3024219290","doi":"10.1109/mce.2020.2986834","title":"LTE IoT Technology Enhancements and Case Studies","year":2020,"lang":"en","type":"article","venue":"IEEE Consumer Electronics Magazine","topic":"IoT Networks and Protocols","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Institute of Technology","funders":"British Columbia Institute of Technology","keywords":"Computer science; Interoperability; Quality of service; Scalability; 3rd Generation Partnership Project 2; LPWAN; Computer network; Internet of Things; Telecommunications; Computer security","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009233113,0.0003879934,0.0001537968,0.0009300919,0.0007721956,0.00167025,0.0005122799,0.001393382,0.001386982],"category_scores_gemma":[0.001726641,0.0001237065,0.0004211296,0.002249585,0.0006273803,0.001566664,0.0007427298,0.000854075,0.0006649914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001638813,"about_ca_system_score_gemma":0.000569714,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008521864,"about_ca_topic_score_gemma":0.009165728,"domain_scores_codex":[0.9990097,0.000283468,0.00006158536,0.00004964386,0.000376909,0.0002186455],"domain_scores_gemma":[0.9992878,0.00035064,0.00007436988,0.00007202913,0.0001467921,0.00006845789],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008250261,0.0006761769,0.0533438,0.0019626,0.0001000219,0.0837968,0.005458821,0.04006749,0.01296341,0.2651604,0.08694974,0.4486957],"study_design_scores_gemma":[0.00003354177,0.0006114901,0.01917317,0.00105767,0.000118258,0.03685077,0.004476644,0.01756943,0.01222866,0.01655355,0.891211,0.0001159001],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2904486,0.04630204,0.01942442,0.006466205,0.0005455287,0.0003192938,0.0009407524,0.0002748207,0.6352785],"genre_scores_gemma":[0.9110749,0.04869372,0.01021045,0.001665088,0.0003399923,0.0001225561,0.0008239018,0.00004283507,0.02702672],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008521864,"threshold_uncertainty_score":0.01694453,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02244211379026936,"score_gpt":0.2746952745621863,"score_spread":0.252253160771917,"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."}}