{"id":"W171351407","doi":"10.48550/arxiv.1401.1977","title":"Robust Energy Management for Green and Survivable IP Networks","year":2014,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"","keywords":"Backup; Computer science; Robustness (evolution); Computer network; Energy consumption; Survivability; Spare part; Quality of service; Network planning and design; Distributed computing; 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":[0.0006453672,0.0009023551,0.0006806695,0.0005760594,0.0003852421,0.001274391,0.001081411,0.000848757,0.001570655],"category_scores_gemma":[0.001164235,0.0003635428,0.0005707382,0.0006517311,0.0006348868,0.001125282,0.001224089,0.0007205853,0.0002592907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00113951,"about_ca_system_score_gemma":0.0005849986,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001806616,"about_ca_topic_score_gemma":0.001448333,"domain_scores_codex":[0.9996787,0.00009358781,0.00001387338,0.00006691366,0.00009901901,0.0000479404],"domain_scores_gemma":[0.9997373,0.0001388183,0.00004621532,0.00002893391,0.00003591195,0.00001275899],"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":[0.00002064753,0.00001481992,0.00007172563,0.00006383036,0.00001356505,0.00003397387,0.00002464189,0.9665446,0.002818074,0.01394845,0.0003510426,0.01609449],"study_design_scores_gemma":[0.000002639851,0.00001228279,0.00003228513,0.00000494231,0.000003017801,0.000008655811,0.000007692437,0.9903532,0.0004121824,0.008522888,0.0006371531,0.000003045679],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0114046,0.0007230613,0.9835252,0.000188278,0.00002929214,0.0000367012,0.00005648808,0.0002084443,0.0038279],"genre_scores_gemma":[0.8920845,0.001274136,0.1010882,0.00008823701,0.00007254718,0.0001971264,0.0001652506,0.0001312579,0.004898628],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001806616,"threshold_uncertainty_score":0.00826776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04123985693859327,"score_gpt":0.1548021678919984,"score_spread":0.1135623109534051,"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."}}