{"id":"W2135743623","doi":"10.1109/cnsr.2008.90","title":"Spectral Regrowth Reduction for Digital Audio Broadcasting Using EER Amplifiers","year":2008,"lang":"en","type":"article","venue":"","topic":"Image and Signal Denoising Methods","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Digital audio broadcasting; Amplifier; Electronic engineering; Bandwidth (computing); Amplitude modulation; Orthogonal frequency-division multiplexing; Frequency modulation; Telecommunications; Engineering; Channel (broadcasting)","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":[0.0002989931,0.0004367322,0.00031133,0.0004721009,0.0002259388,0.0004037761,0.0004428544,0.0004220355,0.00168668],"category_scores_gemma":[0.0008909111,0.0002041504,0.0003897807,0.0003651853,0.0003099293,0.0005057864,0.0003425961,0.0004922053,0.0009025585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002432022,"about_ca_system_score_gemma":0.000214897,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004878418,"about_ca_topic_score_gemma":0.00105099,"domain_scores_codex":[0.9997674,0.00003832779,0.00001372781,0.00004097945,0.0001219839,0.00001755542],"domain_scores_gemma":[0.9996557,0.0001438376,0.00005840712,0.00005722114,0.00007344677,0.00001137513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003875509,0.0001201247,0.0005859548,0.0001291097,0.00003570754,0.0001330075,0.0001834626,0.01667871,0.6056515,0.004132942,0.0006347054,0.3713272],"study_design_scores_gemma":[0.00004644175,0.0005462298,0.002939411,0.00002788237,0.00008039865,0.0009659061,0.0001286473,0.3443449,0.6350155,0.002426537,0.01344097,0.00003714783],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08465412,0.0004592572,0.9111645,0.0001359121,0.00002471015,0.00004277801,0.00002697191,0.0007984065,0.00269329],"genre_scores_gemma":[0.3257935,0.0006290088,0.6666707,0.00009111558,0.00004298007,0.00005343572,0.0001799688,0.000140273,0.006398927],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00168668,"threshold_uncertainty_score":0.005642533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07287702020796195,"score_gpt":0.2972489296030292,"score_spread":0.2243719093950672,"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."}}