{"id":"W3199784387","doi":"10.22215/etd/2008-06194","title":"Performance estimation, code construction and decoding of finite-length low-density parity-check codes","year":2008,"lang":"en","type":"dissertation","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Heritage; Library and Archives Canada","funders":"University of Ottawa","keywords":"Decoding methods; Low-density parity-check code; Computer science; Parity bit; Parity (physics); Statistics; Arithmetic; Mathematics; Algorithm; Physics; Particle physics","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003299247,0.0002874369,0.0004339613,0.0002957981,0.0002612771,0.00007580275,0.0004713399,0.000293545,0.000007893966],"category_scores_gemma":[0.0003216388,0.0003006303,0.00006766155,0.0003389144,0.0001036397,0.0005569511,0.00009984797,0.0003640657,0.000006035896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000619069,"about_ca_system_score_gemma":0.0001744208,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001326733,"about_ca_topic_score_gemma":0.0002356221,"domain_scores_codex":[0.9983008,0.00006172563,0.0005336833,0.0005243783,0.0003574009,0.0002220353],"domain_scores_gemma":[0.998179,0.0002860953,0.0005324884,0.0005092013,0.0004252898,0.00006790696],"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":[0.0002071923,0.0003739172,0.1607333,0.004398537,0.0002467773,0.00003522043,0.01659428,0.001428315,0.006585464,0.03185008,0.002670357,0.7748765],"study_design_scores_gemma":[0.0003229288,0.0001446145,0.03944964,0.0009491905,0.0000506847,0.0001583282,0.0004092455,0.7584327,0.1972765,0.001963925,0.00005243864,0.0007897555],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7521824,0.00007373527,0.2418804,0.00002393042,0.0005816056,0.0002297272,0.000004071196,0.0005837066,0.004440494],"genre_scores_gemma":[0.6930245,0.0004777249,0.3059684,0.0000201285,0.00001923087,0.00001253627,0.00006011823,0.00001580314,0.0004015038],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7740868,"threshold_uncertainty_score":0.9999446,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01506320686093333,"score_gpt":0.2621161058208228,"score_spread":0.2470528989598895,"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."}}