{"id":"W2095641490","doi":"10.1109/pacrim.1991.160715","title":"Bidirectional sequential decoding for convolutional codes","year":2002,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Decoding methods; Sequential decoding; Computer science; Algorithm; Convolutional code; List decoding; Tree (set theory); Code (set theory); Pareto principle; Exponent; Block (permutation group theory); Computation; Theoretical computer science; Block code; Mathematics; Concatenated error correction code; Set (abstract data type); Mathematical optimization; Combinatorics","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":[0.0006879242,0.0006109329,0.0003456827,0.0007454349,0.000465267,0.0009453731,0.0004196013,0.0005138607,0.005127659],"category_scores_gemma":[0.003676276,0.0002198597,0.0003740822,0.001191185,0.0005352813,0.0009034481,0.0008104951,0.0006329109,0.001851472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009726195,"about_ca_system_score_gemma":0.001513128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003724562,"about_ca_topic_score_gemma":0.006020191,"domain_scores_codex":[0.9991845,0.0001831666,0.00004483578,0.00008564598,0.0004034762,0.00009844564],"domain_scores_gemma":[0.9987543,0.0004853732,0.00007949119,0.000224502,0.0004224664,0.0000339488],"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":[0.0002262124,0.00004121264,0.0008592475,0.0002227684,0.00003512205,0.0002131854,0.0001356439,0.1852055,0.02746112,0.380903,0.009743881,0.394953],"study_design_scores_gemma":[0.00002105351,0.00006359042,0.0002617339,0.00004988295,0.00001473561,0.0002952494,0.00002492548,0.7971138,0.02350724,0.158608,0.02001603,0.00002385903],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008865519,0.000395526,0.9769597,0.0001333345,0.00005838801,0.00004283155,0.0001474947,0.0004681867,0.012929],"genre_scores_gemma":[0.46286,0.002255737,0.5061749,0.0003404855,0.0001851567,0.0003513918,0.000856031,0.0004768062,0.02649952],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005127659,"threshold_uncertainty_score":0.01715374,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04709017866936236,"score_gpt":0.2714363201650477,"score_spread":0.2243461414956853,"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."}}