{"id":"W4311731401","doi":"10.1109/ipc53466.2022.9975765","title":"Real-Time Span-Wise Launch Power Optimization for Coherent Optical Systems","year":2022,"lang":"en","type":"article","venue":"2022 IEEE Photonics Conference (IPC)","topic":"Optical Network Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Span (engineering); Power (physics); Computer science; SIGNAL (programming language); Power optimization; Optical power; Optical performance monitoring; Electronic engineering; Engineering; Wavelength-division multiplexing; Optics; Physics; Laser; Structural engineering; Power consumption","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":[0.0004325721,0.0008123523,0.0003622703,0.000340165,0.000214685,0.0004303394,0.0003817629,0.0003499688,0.0006503245],"category_scores_gemma":[0.0008668115,0.0003321625,0.0002337404,0.0003533537,0.0003489951,0.0006157861,0.0005380023,0.0003798414,0.0001779566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000372613,"about_ca_system_score_gemma":0.0004616098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004446293,"about_ca_topic_score_gemma":0.0009338475,"domain_scores_codex":[0.9997539,0.00007935478,0.00001003452,0.00004898277,0.00007641612,0.00003134353],"domain_scores_gemma":[0.9997382,0.000109895,0.00006976641,0.00001808306,0.00005004301,0.0000141276],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001663033,0.0001004922,0.0007739333,0.00007902415,0.00004999377,0.00005887168,0.00009290707,0.8048679,0.1095342,0.004215677,0.0005815787,0.07947912],"study_design_scores_gemma":[0.000004583572,0.00004932756,0.0001423551,0.000001960884,0.000004048029,0.000009361212,0.000004653511,0.9936212,0.005507891,0.0004877973,0.0001617168,0.000005196305],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07083774,0.0003232063,0.9266519,0.0001182989,0.00001738469,0.00002984724,0.0000223043,0.000339509,0.001659848],"genre_scores_gemma":[0.8092011,0.0001969861,0.1891037,0.00004887556,0.00003101621,0.00007616905,0.0000449379,0.0001202234,0.001176953],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008123523,"threshold_uncertainty_score":0.002703547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01478846251255285,"score_gpt":0.2187255476917813,"score_spread":0.2039370851792284,"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."}}