{"id":"W2078719365","doi":"10.1016/j.procs.2013.06.066","title":"Enhanced Adaptive SLA-aware Algorithms for Provisioning Shared Mesh Optical Networks","year":2013,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Saint Mary's University; Dalhousie University","funders":"","keywords":"Computer science; Provisioning; Computer network; Service-level agreement; Distributed computing; Blocking (statistics); Path (computing); Optical mesh network; Shared resource; Quality of service; Algorithm; Telecommunications; Wireless mesh network","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":[0.0001783288,0.0002559164,0.0002558418,0.0001240489,0.0002213253,0.0002495401,0.0008883909,0.000125216,0.00001056409],"category_scores_gemma":[0.0001205202,0.0002275365,0.00005636943,0.0008316457,0.0004226879,0.001042859,0.0003768113,0.0002889523,0.00003709594],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001141143,"about_ca_system_score_gemma":0.00005246403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.292848e-7,"about_ca_topic_score_gemma":7.688802e-7,"domain_scores_codex":[0.9979255,0.000004057779,0.0002838537,0.0005952759,0.0003156824,0.0008756988],"domain_scores_gemma":[0.9988719,0.0002240821,0.00004229941,0.0003316071,0.0003398415,0.0001902633],"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":[0.000006645977,0.0000246325,0.00001842629,0.00004459938,0.00001414176,0.000002095505,0.0001636414,0.3719327,0.001617273,0.004762777,0.0009817935,0.6204313],"study_design_scores_gemma":[0.0001983246,0.0001526847,0.000254057,0.00006831374,0.000004665381,0.000004708906,0.00002744126,0.9919013,0.004160347,0.002850625,0.00006753273,0.0003100461],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.005670465,0.0001255442,0.9908109,0.0001067516,0.0006747792,0.0009384702,0.000002337437,0.00142849,0.0002422247],"genre_scores_gemma":[0.4692826,0.00001287733,0.530117,0.0000537621,0.0001991851,0.0003012292,0.000002111672,0.00002180857,0.000009437187],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6201213,"threshold_uncertainty_score":0.9278667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01332703445611858,"score_gpt":0.2329853778656292,"score_spread":0.2196583434095106,"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."}}