{"id":"W1995404435","doi":"10.1007/s11235-011-9644-8","title":"Lightpath scheduling and routing for green data centres","year":2011,"lang":"en","type":"article","venue":"Telecommunication Systems","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"Computer science; Schedule; Renewable energy; Scheduling (production processes); Energy consumption; Green computing; Energy (signal processing); Distributed computing; Computer network; Cloud computing; Operations management; Operating system","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":[0.0009620657,0.00009430694,0.0001345682,0.00006381072,0.0002836522,0.000132606,0.002403349,0.00003651243,7.708941e-7],"category_scores_gemma":[0.00004183331,0.00008445601,0.00002038009,0.0001410772,0.00002305491,0.00005093174,0.001823238,0.00007814827,0.000008914373],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001855255,"about_ca_system_score_gemma":0.00001456767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006438763,"about_ca_topic_score_gemma":0.00001793692,"domain_scores_codex":[0.9989865,0.0001190211,0.000274751,0.0003157554,0.0001117905,0.000192113],"domain_scores_gemma":[0.9973144,0.0001375233,0.0001747749,0.002260694,0.00005958729,0.00005301416],"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":[0.00002876522,0.0004213969,0.01355514,0.0006051878,0.0003384907,0.00000532377,0.03133977,0.00268468,0.0003831644,0.4681463,0.001895463,0.4805963],"study_design_scores_gemma":[0.0002367694,0.00002895682,0.00147419,0.0000875047,0.000009806859,0.000009192041,0.0004651613,0.9819763,0.00004322745,0.0002734529,0.01525091,0.0001444987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2046775,0.00496656,0.7741275,0.001694529,0.0006110058,0.00125973,0.0000100315,0.0008718552,0.01178126],"genre_scores_gemma":[0.9432226,0.00001583796,0.05632851,0.00004693466,0.00006978118,0.00001702761,0.000008121657,0.000008864413,0.0002823056],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9792916,"threshold_uncertainty_score":0.446606,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1004930677329308,"score_gpt":0.2780495377977901,"score_spread":0.1775564700648593,"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."}}