{"id":"W4235953302","doi":"10.1109/wcnc.2013.6554527","title":"Program","year":2013,"lang":"en","type":"article","venue":"","topic":"PAPR reduction in OFDM","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Leibniz-Gemeinschaft; University of Texas at Dallas; National Chiao Tung University; Southeast University; Shanghai Jiao Tong University; Tsinghua University; University of Waterloo; Shanghai Educational Development Foundation; Beijing University of Posts and Telecommunications; Institute of Computing Technology, Chinese Academy of Sciences; Universidad Carlos III de Madrid; Intel Corporation; University of Nebraska-Lincoln; Chinese Academy of Sciences; Tshwane University of Technology; Università degli Studi di Padova; Beijing Jiaotong University; Deakin University; University of Sydney; National University of Singapore; Indian Institute of Science; Aalto-Yliopisto","keywords":"Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.000005709059,0.00002344239,0.00001906863,0.00001184783,0.000005480007,0.00001387998,0.00002630778,0.00001225466,0.002132968],"category_scores_gemma":[0.000001600305,0.00002019498,0.000008153003,0.00003526956,0.000005360355,0.00005755909,0.000003011953,0.00002283985,0.002992354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006716097,"about_ca_system_score_gemma":7.08474e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006841994,"about_ca_topic_score_gemma":2.980191e-7,"domain_scores_codex":[0.9998581,8.461579e-7,0.00003154744,0.00002395409,0.00002430065,0.00006122177],"domain_scores_gemma":[0.9999118,0.000002006421,0.000001181195,0.00005589869,0.000006772828,0.00002230167],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[1.019035e-7,0.00002124303,0.0004581682,0.0000170655,0.00001866141,3.906431e-7,0.00005330455,0.002415861,0.009717236,0.002330302,0.4997549,0.4852128],"study_design_scores_gemma":[0.0001512811,0.00002657299,0.01362496,0.000004408693,0.00000287214,0.00001440054,0.00009957916,0.0688676,0.02670333,0.001711599,0.8885542,0.0002392284],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.231059,0.00004029036,0.00111987,0.0001394026,0.0004361326,0.0001924582,9.668543e-8,0.002479014,0.7645338],"genre_scores_gemma":[0.9850543,0.000003578237,0.01046184,0.00001721655,0.00006012396,0.0001084933,4.39181e-7,0.0000081368,0.004285866],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7602479,"threshold_uncertainty_score":0.9987792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004945338619082677,"score_gpt":0.2005120887480938,"score_spread":0.1955667501290112,"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."}}