{"id":"W2916163885","doi":"10.1364/ofc.2019.m3j.1","title":"Nonlinear Mitigation Enabling Next Generation High Speed Optical Transport Beyond 100G","year":2019,"lang":"en","type":"article","venue":"","topic":"Optical Network Technologies","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ciena (Canada)","funders":"","keywords":"Transmission (telecommunications); Computer science; Nonlinear system; Nonlinear optical; Optical performance monitoring; Electronic engineering; Nonlinear optics; Optical switch; Telecommunications; Wavelength-division multiplexing; Optoelectronics; Physics; 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":[0.0002678416,0.0006249594,0.0002765481,0.0002926697,0.0005123878,0.0007202059,0.0005379687,0.0006482213,0.002646907],"category_scores_gemma":[0.0003370972,0.000153141,0.0001683149,0.0002076141,0.0007567988,0.001039505,0.0006918837,0.0003742262,0.0005836511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006216659,"about_ca_system_score_gemma":0.0006647159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00067674,"about_ca_topic_score_gemma":0.002178526,"domain_scores_codex":[0.9998735,0.00001651284,0.000002656988,0.00001729887,0.00005873167,0.00003127627],"domain_scores_gemma":[0.9998822,0.00003970109,0.00003899815,0.00001224303,0.00001771895,0.00000906867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000205731,0.0001813766,0.0009917272,0.0004714131,0.00003521327,0.0004530231,0.0002160356,0.02610964,0.5855554,0.3204032,0.002562641,0.06281466],"study_design_scores_gemma":[0.00006608741,0.001302172,0.002219996,0.0003092604,0.00007208139,0.0009002441,0.0003016801,0.2929263,0.4806858,0.1368653,0.08421824,0.0001329373],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3332782,0.01459316,0.5125366,0.00449898,0.000951308,0.000293512,0.0001829531,0.001392132,0.1322731],"genre_scores_gemma":[0.8707829,0.004958368,0.1075882,0.0004166715,0.0002489428,0.00009370634,0.00006594096,0.0000764744,0.01576892],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002646907,"threshold_uncertainty_score":0.008854747,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01456887515590613,"score_gpt":0.2042564361510958,"score_spread":0.1896875609951897,"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."}}