{"id":"W2470812362","doi":"10.1186/s13677-016-0058-8","title":"Green spine switch management for datacenter networks","year":2016,"lang":"en","type":"article","venue":"Journal of Cloud Computing Advances Systems and Applications","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Cloud computing; Energy consumption; CloudSim; Server; Virtualization; Computer network; Software-defined networking; Workload; Efficient energy use; Distributed computing; Operating system; Engineering","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":[0.0003266805,0.0003808431,0.0002946261,0.0003565642,0.0005734775,0.0006424338,0.00079538,0.0002569756,0.0009535581],"category_scores_gemma":[0.0004492566,0.000102943,0.0002011645,0.0002959726,0.0002407041,0.0007386351,0.0004991966,0.0002951076,0.0001104442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008945693,"about_ca_system_score_gemma":0.0006197193,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002536139,"about_ca_topic_score_gemma":0.004846695,"domain_scores_codex":[0.9998146,0.00003249756,0.000008217768,0.00003430064,0.00006298766,0.00004752119],"domain_scores_gemma":[0.9997659,0.00004809342,0.00003982376,0.0000280301,0.00007578722,0.0000424007],"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":[0.0005704504,0.0003093406,0.008328091,0.0002295313,0.00008689834,0.0003349254,0.000286307,0.5532295,0.0910507,0.01686074,0.01030369,0.3184099],"study_design_scores_gemma":[0.00002004773,0.0001170102,0.001507241,0.00001008629,0.000025353,0.00005838873,0.0000664983,0.9779328,0.01245794,0.004125091,0.003666674,0.00001286071],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3758311,0.002091308,0.6078708,0.0008569858,0.0002740901,0.00017117,0.0001810057,0.002908704,0.009814803],"genre_scores_gemma":[0.9826032,0.0002544506,0.01602261,0.00007307728,0.00002727752,0.00002483121,0.00006758743,0.00002515443,0.0009017779],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002536139,"threshold_uncertainty_score":0.006490648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01180760128625469,"score_gpt":0.2592881246260903,"score_spread":0.2474805233398356,"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."}}