{"id":"W4383220181","doi":"10.1109/tvt.2023.3292354","title":"A Permutated Partial Transmit Sequence Scheme for PAPR Reduction in Polar-Coded OFDM-IM Systems","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"PAPR reduction in OFDM","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Beijing Information Science and Technology University","keywords":"Orthogonal frequency-division multiplexing; Additive white Gaussian noise; Algorithm; Reduction (mathematics); Multiplexing; Decoding methods; Frequency domain; Mathematics; Bit error rate; Transmission (telecommunications); Electronic engineering; Computer science; Channel (broadcasting); Telecommunications; Engineering","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":[0.0003072011,0.000623538,0.0002891443,0.0004914814,0.000343262,0.0003650791,0.0004659507,0.0003382086,0.001684276],"category_scores_gemma":[0.0009792229,0.0001778182,0.0002492938,0.0005165726,0.0003871052,0.0006072081,0.0003766745,0.0004420627,0.0006420029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001682849,"about_ca_system_score_gemma":0.0004007602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000272429,"about_ca_topic_score_gemma":0.0004756371,"domain_scores_codex":[0.9996864,0.0001030789,0.00002104414,0.00004190634,0.0001261272,0.00002150007],"domain_scores_gemma":[0.9996136,0.0001099839,0.00006325573,0.00007660385,0.0001213441,0.00001523443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005738683,0.00009289874,0.0006958929,0.0003407874,0.00006400187,0.0003239579,0.0002424933,0.05542745,0.348073,0.03828099,0.001653148,0.5542315],"study_design_scores_gemma":[0.00009038784,0.00120582,0.0008287611,0.00006540368,0.0001102246,0.002002614,0.00007697762,0.6362637,0.3298467,0.0095151,0.01990823,0.00008603787],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02055764,0.0003890661,0.9763095,0.00009174026,0.00006887015,0.00005225608,0.00003994008,0.0003348016,0.002156205],"genre_scores_gemma":[0.4450892,0.0009524142,0.5490408,0.0001864704,0.0001312677,0.0001381786,0.0002025988,0.00005685913,0.004202273],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001684276,"threshold_uncertainty_score":0.005634487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02362020505789106,"score_gpt":0.26051039688905,"score_spread":0.2368901918311589,"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."}}