{"id":"W4256753373","doi":"10.22215/etd/2011-07099","title":"New interative decoding algorithms for low-density parity-check (LDPC) codes","year":2011,"lang":"en","type":"dissertation","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Canadian Heritage; Library and Archives Canada","funders":"","keywords":"Low-density parity-check code; Decoding methods; Computer science; Algorithm; Arithmetic; Mathematics","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":[0.001448395,0.001219546,0.0008114896,0.001734869,0.001197844,0.003097574,0.001800746,0.001539569,0.007578779],"category_scores_gemma":[0.00758091,0.0005842761,0.0008844644,0.001524423,0.0009074316,0.002930406,0.002118233,0.002143248,0.004939105],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001342216,"about_ca_system_score_gemma":0.00192401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002130637,"about_ca_topic_score_gemma":0.005826267,"domain_scores_codex":[0.9982162,0.0003852082,0.0001678896,0.0002617341,0.0007931135,0.0001757639],"domain_scores_gemma":[0.9967128,0.001342278,0.0002124271,0.000628847,0.001021413,0.00008233257],"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":[0.0003824136,0.0002501939,0.001323936,0.0002471691,0.0001177712,0.0001883867,0.0003859033,0.1105017,0.02060162,0.1426812,0.01218952,0.71113],"study_design_scores_gemma":[0.00008752468,0.0001158792,0.0004296128,0.00008555713,0.00005922013,0.0003901847,0.0000962687,0.883275,0.02758058,0.07185363,0.01596104,0.00006539936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008534582,0.0004066676,0.982601,0.0002287713,0.0002547083,0.000102346,0.0001486469,0.001046518,0.006676796],"genre_scores_gemma":[0.09518395,0.0007481397,0.8771161,0.0003504269,0.0002860018,0.0003500381,0.0009606139,0.0004810111,0.02452361],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007578779,"threshold_uncertainty_score":0.02535355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04367872415879104,"score_gpt":0.3256674729943846,"score_spread":0.2819887488355936,"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."}}