{"id":"W2150869859","doi":"10.1109/jlt.2009.2032428","title":"Filter Design for SOA-Assisted SS-WDM Systems Using Parallel Multicanonical Monte Carlo","year":2009,"lang":"en","type":"article","venue":"Journal of Lightwave Technology","topic":"Optical Network Technologies","field":"Engineering","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Wavelength-division multiplexing; Optical filter; Monte Carlo method; Electronic engineering; Bit error rate; Bandwidth (computing); Optical amplifier; Computer science; Filter (signal processing); Channel (broadcasting); Channel spacing; Multiplexing; Optics; Wavelength; Engineering; Physics; Telecommunications; Mathematics","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":[0.000596482,0.0003908292,0.0004799892,0.0003349801,0.0004324896,0.0005366246,0.0005191522,0.0005802772,0.001074078],"category_scores_gemma":[0.001153534,0.000335393,0.0003696633,0.000277045,0.0005383634,0.0004508757,0.0003267297,0.0003448923,0.0001263951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001072476,"about_ca_system_score_gemma":0.00128688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003921037,"about_ca_topic_score_gemma":0.005947062,"domain_scores_codex":[0.9998652,0.00003078936,0.000004379346,0.00001475245,0.00005984827,0.00002497122],"domain_scores_gemma":[0.9993654,0.000364348,0.0000940479,0.00003739009,0.0001044346,0.00003435479],"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":[0.00002825533,0.00001660906,0.000296309,0.00001685826,0.00001324538,0.00001474804,0.00001342295,0.9904743,0.003576916,0.001709417,0.00004918311,0.003790763],"study_design_scores_gemma":[0.000005869003,0.00001107606,0.00003005272,0.000001007289,0.00000253051,0.00000266006,0.000001782596,0.9984527,0.000976417,0.0004368695,0.00007723858,0.00000190351],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3136207,0.0003137306,0.6802151,0.0002584981,0.0000323666,0.00009943142,0.00005655569,0.0003273647,0.005076248],"genre_scores_gemma":[0.8703141,0.0001083651,0.1282644,0.00004443365,0.000009141358,0.0001076362,0.00003187746,0.00004411571,0.001075942],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003921037,"threshold_uncertainty_score":0.007796407,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04490940768039423,"score_gpt":0.2695832575253896,"score_spread":0.2246738498449954,"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."}}