{"id":"W2580925718","doi":"10.1109/access.2016.2646120","title":"Internet of Things (IoT) in 5G Wireless Communications","year":2016,"lang":"en","type":"article","venue":"IEEE Access","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":191,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada; University of Engineering and Technology, Taxila; National University of Sciences and Technology; Zhejiang University; College of Engineering, Michigan State University; Hong Kong University of Science and Technology; University of Michigan; Simon Fraser University; Beijing University of Posts and Telecommunications; University of Engineering and Technology, Lahore; Michigan State University","keywords":"Computer science; Internet of Things; Cloud computing; Wireless sensor network; Wireless; Machine to machine; Analytics; Telecommunications; Data science; Embedded system; Computer network","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":[0.0002795918,0.00007551097,0.0001327247,0.0001215487,0.00003513867,0.0000856322,0.003663252,0.00004185182,0.000002276667],"category_scores_gemma":[0.0000354244,0.00005561264,0.00003420711,0.000320866,0.00007031609,0.0007376429,0.0006948998,0.0000922801,0.00002588976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000353408,"about_ca_system_score_gemma":0.00003866096,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004527557,"about_ca_topic_score_gemma":0.00002200508,"domain_scores_codex":[0.9992067,0.00006031784,0.0002477356,0.000179788,0.000123911,0.0001815034],"domain_scores_gemma":[0.9986646,0.0002313752,0.0001138887,0.0008639963,0.000091842,0.00003429816],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000006720581,0.0001966496,0.05714012,0.00004485525,0.00002266152,0.00000892654,0.005957752,0.000007245201,0.008722498,0.008835732,0.01562173,0.9034351],"study_design_scores_gemma":[0.003864724,0.0002393032,0.1716353,0.002747094,0.00002209237,0.00003748952,0.0000593337,0.3437905,0.3922533,0.04124137,0.04237882,0.001730631],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6246881,0.00007129811,0.3650713,0.00150895,0.004025642,0.0000961152,1.361278e-7,0.00009423717,0.004444156],"genre_scores_gemma":[0.9967296,0.0000143584,0.00269541,0.0002125392,0.0001635259,0.00000485164,2.409606e-7,0.000005532412,0.0001739538],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9017045,"threshold_uncertainty_score":0.6807294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06251635804988134,"score_gpt":0.3155773577462814,"score_spread":0.2530609996964001,"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."}}