{"id":"W4254300512","doi":"10.32920/ryerson.14645199.v1","title":"Adaptive digital predistortion to linearize nonlinear distortion in radio-over-fiber links","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Photonic Communication Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Predistortion; Radio over fiber; Distortion (music); Electronic engineering; Nonlinear distortion; Computer science; Field-programmable gate array; Phase distortion; Nonlinear system; Wireless; Antenna (radio); Compensation (psychology); Engineering; Telecommunications; Physics; Computer hardware; Amplifier; Transmission (telecommunications)","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"],"consensus_categories":[],"category_scores_codex":[0.0001562796,0.0003805221,0.0005178253,0.0002113554,0.00003219166,0.0001554488,0.0004327992,0.000611927,0.0002112059],"category_scores_gemma":[0.00009014254,0.00044537,0.0001625941,0.0003028427,0.00002549315,0.0002893266,0.0005954789,0.001478217,0.0001121302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001357339,"about_ca_system_score_gemma":0.0001102813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001461114,"about_ca_topic_score_gemma":0.0003191809,"domain_scores_codex":[0.9980118,0.00005130846,0.0007993372,0.0005179429,0.0003264734,0.0002931477],"domain_scores_gemma":[0.9982088,0.00008835026,0.0001188071,0.001301495,0.0001256678,0.0001568893],"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":[0.00005781961,0.0001631958,0.0009388286,0.0002805158,0.0001483662,0.00002100722,0.002417104,0.9620991,0.0005500854,0.0000371082,0.0007047475,0.03258216],"study_design_scores_gemma":[0.001161819,0.00009530242,0.008899909,0.001360683,0.00005172983,0.00001952851,0.0008104748,0.9138488,0.001782378,0.0001800572,0.06984592,0.001943463],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4459938,0.003628746,0.4977262,0.0001803663,0.003836384,0.003247129,0.0005724186,0.00207688,0.04273808],"genre_scores_gemma":[0.9813377,0.0001070797,0.01522866,0.00002498444,0.0002434909,0.0003235836,0.0007708512,0.000106552,0.001857099],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5353439,"threshold_uncertainty_score":0.9997998,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01595317824323111,"score_gpt":0.2462280712305657,"score_spread":0.2302748929873346,"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."}}