{"id":"W3039415289","doi":"10.1093/comjnl/bxaa062","title":"Model-Based Comparison of Cloud-Edge Computing Resource Allocation Policies","year":2020,"lang":"en","type":"article","venue":"The Computer Journal","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Fundamental Research Funds for the Central Universities","keywords":"Cloud computing; Computer science; Enhanced Data Rates for GSM Evolution; Resource allocation; Distributed computing; Edge computing; Edge device; Service (business); Focus (optics); Idle; Resource (disambiguation); The Internet; Process (computing); Queueing theory; Computer network; Operating system; Artificial intelligence","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":[0.0008814885,0.0002335723,0.0003983885,0.0001192021,0.0006089538,0.0003678527,0.002301804,0.00006872507,0.000001197032],"category_scores_gemma":[0.00003762573,0.0001764943,0.0001962963,0.0005686347,0.0001130822,0.0002272242,0.0006756149,0.0006472818,0.00001815478],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005332898,"about_ca_system_score_gemma":0.0001779099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005410605,"about_ca_topic_score_gemma":2.407185e-7,"domain_scores_codex":[0.997668,0.0002967894,0.0007510743,0.0002979762,0.00053012,0.0004560153],"domain_scores_gemma":[0.9981998,0.0003087076,0.0005730001,0.000465181,0.0002342679,0.0002190461],"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":[0.0000350147,0.0001323017,0.001519577,0.00005380941,0.00006554244,0.000008515928,0.0234379,0.7721589,0.0008835127,0.004884434,0.07989101,0.1169294],"study_design_scores_gemma":[0.0004447565,0.0001712886,0.0005909051,0.00006674623,0.00001477948,0.00004354804,0.00004662163,0.9915278,0.001378976,0.0008270729,0.004691849,0.0001956894],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07068345,0.0002155439,0.9139028,0.01209834,0.002432088,0.0001123986,1.966403e-7,0.0001434775,0.0004116662],"genre_scores_gemma":[0.8960673,0.000001821739,0.09445397,0.003577762,0.00587074,4.872948e-7,0.000001670135,0.0000180382,0.000008240175],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8253838,"threshold_uncertainty_score":0.7197227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06479046040541213,"score_gpt":0.2935641611250369,"score_spread":0.2287737007196248,"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."}}