{"id":"W2897198428","doi":"10.1109/bsc.2018.8494703","title":"On Base Station Sleeping for Heterogeneous Cloud-Fog Computing Networks","year":2018,"lang":"en","type":"article","venue":"","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Cloud computing; Computer science; Base station; Edge computing; Queueing theory; Computer network; Server; Enhanced Data Rates for GSM Evolution; Distributed computing; Operating system; 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":[0.0007813586,0.0007969387,0.0007854661,0.0004063131,0.001107399,0.001081834,0.001834833,0.0006753738,0.001060907],"category_scores_gemma":[0.001166666,0.000266164,0.0007243918,0.0006641387,0.0006323167,0.001403363,0.0008299383,0.0007594245,0.000166768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001395237,"about_ca_system_score_gemma":0.001505103,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01611588,"about_ca_topic_score_gemma":0.01535643,"domain_scores_codex":[0.9993973,0.0001168562,0.00002002335,0.0001199879,0.0001285116,0.0002173244],"domain_scores_gemma":[0.9996223,0.0001375004,0.00004669157,0.000065951,0.00007840088,0.0000490332],"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":[0.0005815334,0.0001707763,0.0032789,0.0003081418,0.0001589905,0.0008491653,0.0002733721,0.7942234,0.01793615,0.07151079,0.005315382,0.1053934],"study_design_scores_gemma":[0.000007011011,0.00006641898,0.0003559073,0.00001091472,0.00003413118,0.00008295977,0.00003903022,0.9925607,0.001108251,0.004285316,0.001436993,0.00001231424],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1228605,0.004144851,0.8622415,0.0006049862,0.0004946939,0.000153698,0.0001027202,0.0004448719,0.008952196],"genre_scores_gemma":[0.9715798,0.001042534,0.02541029,0.0001987401,0.0000954066,0.00003924047,0.00004430713,0.00002942559,0.001560218],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01611588,"threshold_uncertainty_score":0.03204411,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02253385984438274,"score_gpt":0.2654577316602628,"score_spread":0.24292387181588,"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."}}