{"id":"W3080651932","doi":"10.1109/jphot.2020.3018863","title":"Hybrid OFDM-Digital Filter Multiple Access PONs Utilizing Spectrally Overlapped Digital Orthogonal Filtering","year":2020,"lang":"en","type":"article","venue":"IEEE photonics journal","topic":"Advanced Photonic Communication Systems","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ciena (Canada)","funders":"European Regional Development Fund; Llywodraeth Cymru","keywords":"Passive optical network; Orthogonal frequency-division multiplexing; Upstream (networking); Computer science; Electronic engineering; Transmission (telecommunications); Digital signal processing; Filter (signal processing); Modulation (music); Optical line termination; Power budget; Wavelength-division multiplexing; Telecommunications; Channel (broadcasting); Power (physics); Optics; Engineering; Computer hardware; Physics; Wavelength; Power control","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":["metaepi_narrow","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0002088436,0.0004264931,0.0004695988,0.0001351127,0.0002445336,0.001481807,0.001266606,0.00008811292,0.0002715477],"category_scores_gemma":[0.0001902895,0.0004565359,0.00031685,0.0002695028,0.00006436786,0.002428917,0.0002485299,0.001166287,0.0001397492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002564153,"about_ca_system_score_gemma":0.0001360548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001971525,"about_ca_topic_score_gemma":0.000004939666,"domain_scores_codex":[0.9975013,0.00004208613,0.0008794979,0.0003469163,0.0005385597,0.0006916146],"domain_scores_gemma":[0.9983293,0.0002690036,0.0002328623,0.0005692818,0.0001286348,0.0004708494],"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":[0.001048159,0.0004331479,0.0118209,0.000649748,0.001790561,0.001729041,0.005509347,0.6039084,0.3207126,0.0002445321,0.02430346,0.02785007],"study_design_scores_gemma":[0.003149856,0.0001787959,0.001011201,0.0003450915,0.00005100627,0.003568372,0.0004392441,0.749671,0.07104917,0.0005502368,0.1682873,0.00169877],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9213212,0.0007008173,0.06179979,0.0003028405,0.001424184,0.0004622126,0.0005092659,0.0007463843,0.01273328],"genre_scores_gemma":[0.997313,0.0001792592,0.001711201,0.0002334983,0.0003062356,0.00001894631,0.00003845561,0.0001366054,0.00006285439],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2496634,"threshold_uncertainty_score":0.9997886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04366185190215705,"score_gpt":0.2600324809087058,"score_spread":0.2163706290065488,"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."}}