{"id":"W3088014635","doi":"10.1109/icton51198.2020.9203477","title":"Traffic Prediction in Optical Networks Using Graph Convolutional Generative Adversarial Networks","year":2020,"lang":"en","type":"article","venue":"","topic":"Advanced Optical Network Technologies","field":"Engineering","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"British Columbia Institute of Technology","funders":"","keywords":"Computer science; Spike (software development); Plateau (mathematics); Graph; Optical burst switching; Artificial intelligence; Theoretical computer science; Optical performance monitoring; Physics; Mathematics; Wavelength-division multiplexing","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":[0.0003807287,0.0008902836,0.0004513304,0.0005151977,0.0002309172,0.0004803354,0.0009439618,0.0007691933,0.0009774296],"category_scores_gemma":[0.001253763,0.0004178794,0.0004974123,0.0004939756,0.0005410044,0.0009222953,0.0005244864,0.001374124,0.0002340095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001102071,"about_ca_system_score_gemma":0.0005505077,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0129726,"about_ca_topic_score_gemma":0.01469678,"domain_scores_codex":[0.9998561,0.00002905609,0.000004835806,0.00004814994,0.00002687367,0.00003492501],"domain_scores_gemma":[0.9994943,0.000309663,0.00006508262,0.00002864396,0.00007556551,0.00002671097],"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":[0.00003337642,0.00001579075,0.0007132115,0.00001083698,0.00001193297,0.00003338715,0.00001188287,0.986223,0.0007348768,0.001478432,0.0004963227,0.01023689],"study_design_scores_gemma":[4.825621e-7,0.000002011939,0.00003775344,7.269438e-7,0.000001013192,0.000002428673,8.124786e-7,0.9992859,0.000109974,0.0005277159,0.00003049399,7.729359e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2007391,0.0009538735,0.7890263,0.0010196,0.0002160158,0.00005131193,0.0005200873,0.00233407,0.005139627],"genre_scores_gemma":[0.9762408,0.0002236729,0.02018788,0.0001887321,0.0000451557,0.00002928468,0.0003107476,0.0000631331,0.002710482],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0129726,"threshold_uncertainty_score":0.02579415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0169172297923884,"score_gpt":0.2131859788008081,"score_spread":0.1962687490084197,"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."}}