{"id":"W4391577079","doi":"10.1364/ol.509441","title":"Fiber-optic spectrum monitoring of wavelength-division-multiplexed telecommunication signals with MHz update rates","year":2024,"lang":"en","type":"article","venue":"Optics Letters","topic":"Optical Network Technologies","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wavelength-division multiplexing; Computer science; Frequency-division multiplexing; Multiplexing; Photodetection; Optics; Sampling (signal processing); Dynamic range; Electronic engineering; Wavelength; Telecommunications; Channel (broadcasting); Physics; Engineering; Photodetector; Orthogonal frequency-division multiplexing; Detector","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000335905,0.000304568,0.0001853789,0.000318772,0.0001218321,0.000235701,0.0004491291,0.0002764253,0.0003363671],"category_scores_gemma":[0.0008677205,0.0001374498,0.00007845585,0.0002814839,0.0003089059,0.0006938345,0.0003151592,0.0002121176,0.0000783186],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002291866,"about_ca_system_score_gemma":0.0001226597,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002830474,"about_ca_topic_score_gemma":0.00059018,"domain_scores_codex":[0.9997423,0.00005616368,0.00001269874,0.00005782125,0.0001098375,0.00002103731],"domain_scores_gemma":[0.9995555,0.0001788088,0.0001365174,0.00006331404,0.00004974944,0.00001598915],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001892015,0.00004798413,0.003486333,0.00006336092,0.00001013745,0.00009107732,0.00007730944,0.003303989,0.9566823,0.001378256,0.0001035022,0.03456663],"study_design_scores_gemma":[0.00002890923,0.0002274584,0.004430529,0.000008505162,0.00001761185,0.000409488,0.00003239704,0.1312707,0.8616543,0.0007494714,0.001148994,0.00002164209],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.878336,0.0003716855,0.1196276,0.0001133071,0.00002173706,0.00003135846,0.00005424384,0.0002553984,0.001188476],"genre_scores_gemma":[0.9618202,0.0001005465,0.03773428,0.00002338433,0.00001194244,0.00001928507,0.00001525483,0.000008472709,0.0002666743],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0004491291,"threshold_uncertainty_score":0.001776457,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00995664749275359,"score_gpt":0.2274995048895616,"score_spread":0.217542857396808,"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."}}