{"id":"W4390485514","doi":"10.1109/acp/poem59049.2023.10369637","title":"Performance Improvement by Channel gOSNR Waterfilling","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Photonic Communication Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"Computer science; Channel (broadcasting); Computer network","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001067979,0.00008219739,0.00008022135,0.00004207125,0.00004942794,0.00001225252,0.0001749113,0.00002710126,0.00006453925],"category_scores_gemma":[0.000002228667,0.00007556747,0.00001826448,0.0001868646,0.000007495364,0.00009627436,0.00005554179,0.0000714543,0.000606278],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004972519,"about_ca_system_score_gemma":0.000002698292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008474991,"about_ca_topic_score_gemma":0.000002080838,"domain_scores_codex":[0.9994597,0.000004169238,0.0001599751,0.00008593573,0.00009011474,0.0002000503],"domain_scores_gemma":[0.999577,0.00001836785,0.00001225717,0.0003390149,0.00001517979,0.00003814897],"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":[0.000005937226,0.00002250742,0.0002932659,0.0003533442,0.00009141374,0.000001583482,0.002018522,0.3982806,0.502614,0.0002516645,0.04712389,0.04894331],"study_design_scores_gemma":[0.0001395327,0.00001451289,0.00006124799,0.00001643386,0.000001442688,8.432418e-7,0.0001718631,0.7727709,0.1340638,0.00001760822,0.09260035,0.0001414984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9524693,0.0002252268,0.009265948,0.0001636579,0.0006647836,0.00034671,0.00001327752,0.002953654,0.03389739],"genre_scores_gemma":[0.993711,0.0005233887,0.0001792978,0.00002375947,0.0000219399,0.0000854419,0.00002684295,0.00002657803,0.005401777],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3744903,"threshold_uncertainty_score":0.779268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01293963300202556,"score_gpt":0.2141678939714362,"score_spread":0.2012282609694107,"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."}}