{"id":"W3086857118","doi":"10.1364/cleo_si.2020.sth3l.2","title":"Experimental Demonstration of Hybrid OFDM-Digital Filter Multiple Access PONs for 5G and Beyond Networks","year":2020,"lang":"en","type":"article","venue":"Conference on Lasers and Electro-Optics","topic":"Advanced Photonic Communication Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ciena (Canada)","funders":"","keywords":"Orthogonal frequency-division multiplexing; Passive optical network; Electronic engineering; Computer science; Optical line termination; Digital signal processing; Multiplexing; Access network; Robustness (evolution); Engineering; Telecommunications; Wavelength-division multiplexing; Channel (broadcasting); Wavelength; Optics","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":[0.00003001588,0.0001210472,0.0001647398,0.00002328472,0.00005011314,0.00008677659,0.0001190451,0.00003581351,0.000006070236],"category_scores_gemma":[0.00001582649,0.000126377,0.00002542304,0.00005145868,0.0000528112,0.0002081161,0.00002452032,0.0001048837,5.117845e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001588665,"about_ca_system_score_gemma":0.00001956613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001404841,"about_ca_topic_score_gemma":0.000002241032,"domain_scores_codex":[0.9994475,0.000008531122,0.0001867108,0.0001382042,0.00006234054,0.000156768],"domain_scores_gemma":[0.9995789,0.0001022693,0.00004857638,0.0001398568,0.00004262675,0.00008776822],"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":[0.001315622,0.0003970359,0.004899602,0.0008706609,0.0005776039,0.00001275199,0.004125696,0.153428,0.7242115,0.04817345,0.004597988,0.05739017],"study_design_scores_gemma":[0.0005155955,0.0002206711,0.00003644696,0.00002051476,0.000008297053,0.000004543142,0.000242757,0.8083643,0.189935,0.0001381293,0.0003700148,0.0001437401],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8675641,0.000671722,0.1259314,0.000344136,0.0000861447,0.0006013787,0.0001009795,0.0001156272,0.004584536],"genre_scores_gemma":[0.9990593,0.0001524332,0.0005670264,0.00007623228,0.00002751875,0.00003426827,0.00005267005,0.00001724032,0.0000133646],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6549363,"threshold_uncertainty_score":0.5153505,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03393301788737407,"score_gpt":0.2625034179430025,"score_spread":0.2285704000556285,"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."}}