{"id":"W2809436939","doi":"10.1002/ett.3446","title":"A collaborative mobile edge computing and user solution for service composition in 5G systems","year":2018,"lang":"en","type":"article","venue":"Transactions on Emerging Telecommunications Technologies","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":97,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Gnowit (Canada)","funders":"","keywords":"Computer science; Cloud computing; Computer network; Mobile edge computing; Enhanced Data Rates for GSM Evolution; Mobile QoS; Mobile computing; Services computing; Quality of service; Edge computing; Context (archaeology); Distributed computing; Service (business); Workflow; Service delivery framework; Web service; World Wide Web; Operating system; Database; Telecommunications","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":[0.001246546,0.000575954,0.0005806158,0.0006106007,0.001516066,0.001704857,0.001394014,0.001495492,0.003205546],"category_scores_gemma":[0.001300683,0.000282132,0.000707375,0.0007163385,0.0005341017,0.001632525,0.002481276,0.0008245611,0.0007031336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000808335,"about_ca_system_score_gemma":0.001451571,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003159644,"about_ca_topic_score_gemma":0.00379682,"domain_scores_codex":[0.9988825,0.0003144335,0.00006503149,0.0002056167,0.0003560295,0.0001763869],"domain_scores_gemma":[0.9995746,0.00009524035,0.00003958552,0.00009021218,0.0001272532,0.0000731102],"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":[0.00088488,0.0008324384,0.003966521,0.0003144308,0.0002023443,0.001840138,0.001326796,0.3786575,0.0572382,0.2147962,0.008446923,0.3314937],"study_design_scores_gemma":[0.00002135786,0.0001001384,0.0002078221,0.00001718596,0.0000281099,0.000169096,0.000145555,0.9685389,0.006129892,0.01473541,0.0098888,0.00001765355],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05536843,0.0002653493,0.9313536,0.0005036852,0.0001050355,0.0002250655,0.00003773092,0.0009403902,0.01120068],"genre_scores_gemma":[0.7019926,0.0002045978,0.2895571,0.0001944888,0.00005359973,0.0001480519,0.00009457284,0.00007223047,0.007682714],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003205546,"threshold_uncertainty_score":0.01072359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01148473570654696,"score_gpt":0.2783627134656595,"score_spread":0.2668779777591125,"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."}}