{"id":"W2372645900","doi":"","title":"An improved nonlinear compensation algorithm in broadband PCS channel","year":2006,"lang":"en","type":"article","venue":"Journal of Anshan University of Science and Technology","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Discovery Air (Canada)","funders":"","keywords":"Channel (broadcasting); Algorithm; Computer science; Bit error rate; Compensation (psychology); Distortion (music); Broadband; Transmission (telecommunications); Nonlinear distortion; Nonlinear system; Telecommunications; Bandwidth (computing); Amplifier","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":[0.0003277874,0.000460244,0.000316048,0.0002931944,0.0003971854,0.000365625,0.0004594471,0.0004728423,0.001604822],"category_scores_gemma":[0.0007659153,0.0001554671,0.0002782394,0.0003601338,0.000307009,0.0007574762,0.0003191047,0.0005707725,0.0004779873],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004272702,"about_ca_system_score_gemma":0.0006284257,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003610266,"about_ca_topic_score_gemma":0.004957362,"domain_scores_codex":[0.9997233,0.00004761983,0.00001442044,0.00005041028,0.00013537,0.00002888647],"domain_scores_gemma":[0.9997662,0.00004330248,0.00002353563,0.00002835486,0.0001301827,0.000008584335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005974257,0.00009284593,0.001924368,0.000187289,0.00006547702,0.0002049413,0.0002947032,0.2132588,0.1794442,0.0225135,0.00276142,0.578655],"study_design_scores_gemma":[0.00003608752,0.0001663862,0.0009492595,0.00001022225,0.00002840883,0.0002369233,0.00003113352,0.9473668,0.0451442,0.001573581,0.00442276,0.00003419733],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03791956,0.0002522506,0.9584378,0.0001247638,0.00009953902,0.00004763634,0.00002467164,0.000419388,0.002674435],"genre_scores_gemma":[0.4420011,0.0003894958,0.5443832,0.00009170425,0.0001025089,0.00008314113,0.0001222198,0.0000538716,0.01277285],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003610266,"threshold_uncertainty_score":0.007178485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008985560932943245,"score_gpt":0.2309470977118704,"score_spread":0.2219615367789272,"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."}}