{"id":"W2120955921","doi":"10.1007/s10470-007-9038-8","title":"An efficient crest factor reduction technique for wideband applications","year":2007,"lang":"en","type":"article","venue":"Analog Integrated Circuits and Signal Processing","topic":"PAPR reduction in OFDM","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Simon Fraser University","funders":"Simon Fraser University; Kwangwoon University","keywords":"Crest factor; Reduction (mathematics); Wideband; Amplifier; Computer science; Electronic engineering; Power (physics); Algorithm; Mathematics; Bandwidth (computing); Engineering; Telecommunications; Physics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002458641,0.0001739042,0.0001532192,0.0002147824,0.0002577775,0.0001078792,0.0001010969,0.0001402545,0.00001901891],"category_scores_gemma":[0.000009720849,0.0001610283,0.00003508996,0.0003836,0.00008140468,0.0001844568,0.000003894951,0.0002057878,0.000002113741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008611711,"about_ca_system_score_gemma":0.00004254194,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001473995,"about_ca_topic_score_gemma":0.000005696465,"domain_scores_codex":[0.9990511,0.00001100061,0.0002856051,0.0002631677,0.0001112795,0.0002778307],"domain_scores_gemma":[0.9994739,0.00003080343,0.00005674829,0.0001136751,0.0001935494,0.0001313062],"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":[0.000008037588,0.00004854895,0.00007112113,0.0001206637,0.00002053362,0.000001081767,0.0003297081,0.007423974,0.7599343,0.0003724361,0.00008560812,0.231584],"study_design_scores_gemma":[0.0006782825,0.000273756,0.001089237,0.0003228193,0.0001001399,0.0002768514,0.002629207,0.1048621,0.8733483,0.002515713,0.01287129,0.001032331],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05700723,0.0006479045,0.9402168,0.00001327496,0.00007461496,0.0005135529,0.00002015231,0.000330497,0.001175983],"genre_scores_gemma":[0.9980464,0.00001702675,0.001417602,0.0000151311,0.0002013709,0.0001823648,0.00004610904,0.0000371462,0.00003682774],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9410392,"threshold_uncertainty_score":0.6566543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01563949387286772,"score_gpt":0.2658787501246501,"score_spread":0.2502392562517823,"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."}}