{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002597854,0.0001934425,0.0002134006,0.0005908278,0.0009190763,0.0001435324,0.001138451,0.0001478933,0.000001396371],"category_scores_gemma":[0.000006609559,0.0001963021,0.00003614409,0.00202312,0.0001357474,0.0004170051,0.00007048862,0.0003029384,0.00001001234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008467832,"about_ca_system_score_gemma":0.00004762804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003057625,"about_ca_topic_score_gemma":0.001051776,"domain_scores_codex":[0.9987226,0.0001069327,0.0003464317,0.0003945353,0.0001228532,0.0003066169],"domain_scores_gemma":[0.9980733,0.0003371956,0.0001419709,0.001073051,0.0003458238,0.000028665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002099161,0.00197445,0.0006854256,0.0006125525,0.0003657504,0.000002761538,0.04047678,0.0463957,0.03185758,0.1392569,0.0003500255,0.7378122],"study_design_scores_gemma":[0.001616783,0.0008036371,0.001674964,0.0005656354,0.00005610426,0.00003217928,0.01475398,0.9331429,0.02271314,0.003804097,0.02001499,0.0008216274],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05976585,0.0007187572,0.9300539,0.006513351,0.0002000825,0.001000286,0.00001808978,0.001396355,0.0003333404],"genre_scores_gemma":[0.8823848,0.0001973946,0.1167539,0.0001818539,0.0000136655,0.000432384,0.00001304542,0.00001367901,0.000009202242],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8867472,"threshold_uncertainty_score":0.8004969,"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."}}