{"id":"W1526537285","doi":"10.1109/glocom.2001.965137","title":"A new turbo coded QAM scheme with very low decoding complexity for ADSL system","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ciena (Canada)","funders":"","keywords":"Turbo code; Computer science; Turbo; Decoding methods; QAM; Serial concatenated convolutional codes; Asymmetric digital subscriber line; Turbo equalizer; Quadrature amplitude modulation; Convolutional code; Algorithm; Concatenated error correction code; Bit error rate; Electronic engineering; Computer engineering; Digital subscriber line; Computer network; Engineering; Block code","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":[0.0003295882,0.0003869614,0.0003470153,0.0004370231,0.0003934128,0.0003583577,0.0004083795,0.0006683026,0.001835724],"category_scores_gemma":[0.000772023,0.000159102,0.000257497,0.0004020697,0.0005289312,0.0006647485,0.000416617,0.0004803849,0.0009461918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005005713,"about_ca_system_score_gemma":0.0008139515,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000565343,"about_ca_topic_score_gemma":0.0007357218,"domain_scores_codex":[0.9997622,0.00006652291,0.00001564892,0.00002767019,0.0001034656,0.00002452224],"domain_scores_gemma":[0.9996147,0.00007089436,0.00005103141,0.00007164951,0.0001554853,0.00003621138],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006627837,0.00008046204,0.001260793,0.0005400099,0.00008508947,0.001043397,0.0005111692,0.06665139,0.4833858,0.1004162,0.00812293,0.33724],"study_design_scores_gemma":[0.0002625485,0.0008972316,0.001297804,0.0000955645,0.0001163613,0.002917989,0.00006330534,0.7348565,0.1886985,0.025091,0.04551607,0.0001870925],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07517988,0.001462399,0.9091371,0.0009489252,0.0002680075,0.0001457448,0.0001483829,0.001278551,0.01143108],"genre_scores_gemma":[0.6019633,0.0006917073,0.388163,0.0004556324,0.0001444714,0.0001209479,0.0001251212,0.00005643828,0.008279379],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001835724,"threshold_uncertainty_score":0.006141126,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03816725643447541,"score_gpt":0.2378159572612875,"score_spread":0.1996487008268121,"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."}}