{"id":"W2502577124","doi":"10.1016/j.procs.2016.08.039","title":"Energy Aware Scheduling and Routing of Periodic Lightpath Demands in Optical Grid Networks","year":2016,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Energy consumption; Computer network; Scheduling (production processes); Exploit; Anycast; Distributed computing; Routing (electronic design automation); Grid; Schedule; Flexibility (engineering); Mathematical optimization","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002000293,0.0001262564,0.0001791853,0.0001351303,0.00005627787,0.00003590321,0.0003392786,0.00007246133,8.948242e-7],"category_scores_gemma":[0.00005556066,0.00009197838,0.00001656933,0.0005967967,0.0004822982,0.0003343319,0.0003062427,0.0001141058,7.28458e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004875819,"about_ca_system_score_gemma":0.00002710838,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":7.398567e-7,"about_ca_topic_score_gemma":0.000002149637,"domain_scores_codex":[0.9988882,0.000003856477,0.0002270513,0.0002971505,0.0001663641,0.0004174121],"domain_scores_gemma":[0.9995512,0.0001233481,0.00002853126,0.0001649721,0.00005119162,0.00008072473],"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":[0.000007288603,0.00002330097,0.0189072,0.00006390223,0.000006152142,0.00001651901,0.0002026128,0.3058081,0.003404132,0.01699298,0.00001097434,0.6545568],"study_design_scores_gemma":[0.0001547726,0.00004011405,0.002815143,0.0001902826,0.000001640062,0.00001115305,0.000009867252,0.9933085,0.002521889,0.0007846375,0.00002000719,0.0001419242],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.23458,0.0002851501,0.764582,0.00006303089,0.00020178,0.00003778535,3.006155e-7,0.0002017728,0.00004822045],"genre_scores_gemma":[0.8418492,0.0001611663,0.1578524,0.00001537183,0.0001048314,0.000006919459,1.255215e-7,0.000009124484,8.974421e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6875005,"threshold_uncertainty_score":0.3750769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005502461691244937,"score_gpt":0.1958153246203478,"score_spread":0.1903128629291028,"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."}}