{"id":"W1998696172","doi":"10.1109/vetecf.2010.5594462","title":"A Modified Belief Propagation Algorithm Based on Attenuation of the Extrinsic LLR","year":2010,"lang":"en","type":"article","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Communications Research Centre Canada","funders":"","keywords":"Belief propagation; Algorithm; Low-density parity-check code; Decoding methods; Logarithm; Sign (mathematics); Computer science; Joint (building); Bit error rate; Sequential decoding; Message passing; Berlekamp–Welch algorithm; Mathematics; Block code; Error floor; Engineering; Parallel computing","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003945961,0.00008144672,0.0000753872,0.00008778566,0.00007671611,0.00003505848,0.0006263003,0.00005955656,0.000007855764],"category_scores_gemma":[0.0001394443,0.00005436191,0.00004973554,0.0003826067,0.00003339841,0.0001600097,0.00009378608,0.0001989012,0.000007636909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002116043,"about_ca_system_score_gemma":0.00007346678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008176119,"about_ca_topic_score_gemma":0.00005643112,"domain_scores_codex":[0.9991268,0.00005658459,0.0001647549,0.0002175519,0.0003259196,0.0001083985],"domain_scores_gemma":[0.9988515,0.00009779494,0.0001288248,0.000752244,0.0001468349,0.00002278497],"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":[0.000006384858,0.0002301331,0.0009147569,0.0000137104,0.000004167751,9.489219e-7,0.0003960939,0.0006305996,0.09461112,0.05389943,0.0007266578,0.848566],"study_design_scores_gemma":[0.0001150604,0.00006967681,0.005840247,0.00001611785,0.000002046812,0.000001700079,0.000002958783,0.7912633,0.2005601,0.001988816,0.000069266,0.00007067851],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04765946,8.981434e-7,0.9448966,0.001233888,0.0004610327,0.0003161058,5.422737e-7,0.000354743,0.005076683],"genre_scores_gemma":[0.8369901,1.3724e-7,0.16251,0.0002560973,0.00002734148,0.00002198375,6.463924e-7,0.000005271488,0.0001884319],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8484953,"threshold_uncertainty_score":0.2216814,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01387850710307635,"score_gpt":0.2441717107211512,"score_spread":0.2302932036180748,"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."}}