{"id":"W3098702051","doi":"","title":"4 The ADMM penalized decoder for LDPC codes∗","year":2014,"lang":"en","type":"article","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Low-density parity-check code; Computer science; Forward error correction; Decoding methods; Algorithm; Turbo code; Theoretical computer science; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001020491,0.00009968027,0.0001085524,0.00003285278,0.0002960852,0.0002083235,0.001220177,0.00004114917,0.00001050084],"category_scores_gemma":[0.0003942302,0.00006194483,0.00007898024,0.0001309706,0.00003346077,0.0001590732,0.0002021896,0.00007726788,0.00003738562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002161582,"about_ca_system_score_gemma":0.00003217454,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002682495,"about_ca_topic_score_gemma":0.0001751439,"domain_scores_codex":[0.9990608,0.00007388794,0.0001679215,0.0002645488,0.0001583168,0.0002745344],"domain_scores_gemma":[0.9980384,0.00100333,0.0000661532,0.0007207291,0.000117645,0.00005370669],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00001432007,0.00002594271,0.0002906781,0.00000821295,0.00001373611,4.539911e-7,0.0002626101,0.000008827056,0.001152519,0.7767347,0.08058164,0.1409063],"study_design_scores_gemma":[0.0004401024,0.0001991791,0.0002510567,0.00001510691,0.000007039384,0.00001618221,0.00002222886,0.4122882,0.03503276,0.1120853,0.4393481,0.0002947231],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0007890121,0.00003111384,0.9740145,0.002406229,0.0003773047,0.0002506371,3.068556e-7,0.0009413909,0.02118951],"genre_scores_gemma":[0.4807825,0.000006803386,0.5120165,0.001449509,0.00008540045,0.0001356967,7.074744e-7,0.00001531426,0.005507619],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.6646494,"threshold_uncertainty_score":0.2526037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01409845574576276,"score_gpt":0.2815434562247819,"score_spread":0.2674450004790192,"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."}}