{"id":"W1997847569","doi":"10.1109/lcomm.2012.020212.112560","title":"Turbo Receiver for DS-SS Systems Employing Parity Bit Selected Spreading Codes","year":2012,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Turbo code; Additive white Gaussian noise; Algorithm; Parity bit; Computer science; Bit error rate; Turbo; Fading; Decoding methods; Turbo equalizer; Low-density parity-check code; Electronic engineering; Telecommunications; Mathematics; Block code; Concatenated error correction code; Channel (broadcasting); 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":[0.000746853,0.0003976774,0.0004130973,0.0003447296,0.0003160962,0.0004734929,0.0004589476,0.0006245244,0.001495893],"category_scores_gemma":[0.001666141,0.0001750083,0.0003220344,0.000262513,0.0003516437,0.0005483883,0.0004137379,0.0005853999,0.001062867],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002775288,"about_ca_system_score_gemma":0.0007567432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007291763,"about_ca_topic_score_gemma":0.001194671,"domain_scores_codex":[0.9995691,0.0001281167,0.00002592772,0.00003177816,0.0002125221,0.00003239825],"domain_scores_gemma":[0.9991448,0.0002724369,0.00007634496,0.00009710528,0.0003754617,0.00003389933],"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":[0.001359152,0.0001048058,0.003237457,0.0007473073,0.0001904719,0.001278827,0.0004340945,0.105152,0.3434044,0.07480273,0.005934641,0.4633542],"study_design_scores_gemma":[0.00007556991,0.0009668521,0.001071956,0.00008599824,0.0001561453,0.002371556,0.00006579154,0.7886392,0.169971,0.007715084,0.02876564,0.0001152328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03265255,0.00137171,0.9595757,0.0002361381,0.0001578779,0.00006663783,0.00004285581,0.0005754316,0.005321043],"genre_scores_gemma":[0.6340608,0.001740221,0.3480527,0.0003028092,0.0001674366,0.0001055894,0.0001303663,0.0000689848,0.01537108],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001495893,"threshold_uncertainty_score":0.005004287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08667197456054516,"score_gpt":0.3329946082431082,"score_spread":0.2463226336825631,"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."}}