{"id":"W2110288531","doi":"10.1109/tcomm.2013.021913.120149","title":"Relaxed Half-Stochastic Belief Propagation","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Decoding methods; Belief propagation; Computer science; Code word; Algorithm; Binary number; Throughput; Low-density parity-check code; Bit error rate; Coding (social sciences); Sequential decoding; Theoretical computer science; Wireless; Block code; Mathematics; Arithmetic; Telecommunications","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002222813,0.0001741896,0.0001444467,0.0002695121,0.0007160941,0.0001811446,0.002343477,0.0000999482,0.00005424935],"category_scores_gemma":[0.00002686664,0.0001805744,0.00009970181,0.0007260161,0.0001230409,0.0008147699,0.00001524208,0.000539982,0.0008009557],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001300228,"about_ca_system_score_gemma":0.00007576332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003274315,"about_ca_topic_score_gemma":0.0001713206,"domain_scores_codex":[0.9986574,0.0001924665,0.0003376943,0.0003183277,0.0002459383,0.0002481719],"domain_scores_gemma":[0.9956638,0.0004257461,0.0001215153,0.003426152,0.0002605339,0.0001022289],"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":[0.00001642308,0.00336888,0.00002659132,0.00004615309,0.0001720472,0.000002607116,0.007022297,0.01713692,0.04693823,0.09257768,0.00750503,0.8251871],"study_design_scores_gemma":[0.0006853818,0.0005039716,0.0006370166,0.0002747747,0.00006610601,0.00008891283,0.0002033709,0.9170378,0.0502031,0.02679921,0.002446345,0.001054021],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0006784258,0.00004865264,0.9853622,0.007601485,0.0003303887,0.0006738572,0.000002527776,0.001560496,0.003741972],"genre_scores_gemma":[0.867345,0.00003783241,0.1308237,0.0002455675,0.00001093578,0.0007589692,0.000002924766,0.00002045865,0.0007545765],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8999009,"threshold_uncertainty_score":0.9999771,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03033599025639153,"score_gpt":0.2719357193684541,"score_spread":0.2415997291120625,"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."}}