{"id":"W2166478505","doi":"10.1109/tcomm.2007.910589","title":"Estimation of Bit and Frame Error Rates of Finite-Length Low-Density Parity-Check Codes on Binary Symmetric Channels","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":52,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Low-density parity-check code; Algorithm; Decoding methods; Binary symmetric channel; Bit error rate; Parity bit; Error detection and correction; Binary number; Computer science; Mathematics; Arithmetic","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":[0.0008784763,0.0001797364,0.0002861127,0.0008401995,0.0003483202,0.00003659502,0.001120086,0.0001450751,0.000004140846],"category_scores_gemma":[0.0001310382,0.0001913974,0.00009791093,0.001489427,0.0002564748,0.0003093678,0.00003055368,0.0004963998,0.000008177143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006508503,"about_ca_system_score_gemma":0.00005810626,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002641483,"about_ca_topic_score_gemma":0.0001579634,"domain_scores_codex":[0.9985354,0.0001998615,0.0005120534,0.0002787408,0.0002713783,0.0002025691],"domain_scores_gemma":[0.9948038,0.002612297,0.0002875126,0.0019773,0.0002392857,0.00007978523],"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":[0.0005007821,0.01546816,0.001729065,0.0009061836,0.0006573382,0.00001449364,0.02014942,0.1626291,0.04811438,0.100588,0.0007443324,0.6484988],"study_design_scores_gemma":[0.0003848213,0.000719309,0.003396064,0.0003380794,0.00005724129,0.00001178112,0.0001922951,0.6049253,0.3854401,0.004117202,0.00007912529,0.0003387297],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1459022,0.0001057616,0.8520268,0.0007609919,0.0001860949,0.0002936753,0.00002067791,0.0002648734,0.0004389063],"genre_scores_gemma":[0.9053879,0.0002592672,0.09417791,0.00008501034,0.000005154523,0.00002745089,0.000004697315,0.00001430991,0.00003834899],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7594856,"threshold_uncertainty_score":0.7804961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04991802552880289,"score_gpt":0.3278226457086265,"score_spread":0.2779046201798236,"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."}}