{"id":"W2102981938","doi":"10.1109/lcomm.2002.803481","title":"Bootstrap decoding of low-density parity-check codes","year":2002,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Low-density parity-check code; Decoding methods; Erasure; Computer science; Algorithm; Parity bit; List decoding; Sequential decoding; Mathematics; Arithmetic; Theoretical computer science; Concatenated error correction code; Block code","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":[0.0007984914,0.000424548,0.0005500899,0.0005185698,0.0004790535,0.0006529067,0.0006256796,0.0007080906,0.001167803],"category_scores_gemma":[0.005326253,0.0002212227,0.0002919292,0.0004571546,0.0005994895,0.0006591612,0.0008668292,0.00079865,0.001039296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003946023,"about_ca_system_score_gemma":0.0005484016,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005423749,"about_ca_topic_score_gemma":0.0007303892,"domain_scores_codex":[0.9992228,0.0003069034,0.00002822277,0.00005643589,0.0003058907,0.00007979134],"domain_scores_gemma":[0.9979345,0.001021233,0.0001260265,0.0003692565,0.0004941469,0.00005494596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008323335,0.0001397854,0.003093193,0.0003299941,0.000074544,0.0008094808,0.0003596677,0.3267079,0.1270549,0.2227805,0.006439803,0.3113781],"study_design_scores_gemma":[0.00003147447,0.00009789605,0.0003900921,0.00002605066,0.00001237295,0.0001662228,0.000017977,0.8938949,0.05502909,0.04718527,0.0031217,0.00002701454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1337294,0.0005299303,0.8554906,0.0002610016,0.00009157998,0.00006454231,0.0001831436,0.00120014,0.008449603],"genre_scores_gemma":[0.758146,0.00044854,0.2369201,0.0001302591,0.00007375442,0.00013256,0.0005202815,0.0001169706,0.003511592],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001167803,"threshold_uncertainty_score":0.00422287,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08314543522971805,"score_gpt":0.3042154743104801,"score_spread":0.221070039080762,"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."}}