{"id":"W2973003915","doi":"10.1109/focs46700.2020.00050","title":"LDPC Codes Achieve List Decoding Capacity","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Israel Science Foundation; National Science Foundation","keywords":"Low-density parity-check code; Decoding methods; Mathematics; Code (set theory); List decoding; Discrete mathematics; Combinatorics; Concatenated error correction code; Algorithm; Computer science; Block code","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001333153,0.0008459049,0.0008711523,0.001144884,0.001085987,0.00175152,0.001074038,0.001293422,0.002614773],"category_scores_gemma":[0.01535363,0.0004570174,0.000652332,0.001269327,0.001993438,0.002785438,0.002947432,0.002493184,0.001342489],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001293718,"about_ca_system_score_gemma":0.001125176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001251201,"about_ca_topic_score_gemma":0.0008269283,"domain_scores_codex":[0.9979595,0.0003626517,0.0001003144,0.0002963125,0.0008950569,0.0003861328],"domain_scores_gemma":[0.9877543,0.007246926,0.001205944,0.001975356,0.001392577,0.0004248622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003690045,0.0001382881,0.003387237,0.0004202288,0.0001139379,0.0005530833,0.0005781451,0.3000088,0.04355345,0.5952124,0.006789129,0.04887632],"study_design_scores_gemma":[0.00006471042,0.0001526968,0.0008461279,0.00007362699,0.00004195716,0.0005942578,0.00009270047,0.612137,0.05263113,0.328659,0.0046291,0.0000777063],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2111286,0.0008599481,0.7466741,0.001325889,0.00007743674,0.0001633496,0.001043578,0.002514203,0.03621304],"genre_scores_gemma":[0.9710031,0.0004973004,0.02368641,0.0003464379,0.00006091489,0.0001684373,0.0003525036,0.0002132731,0.003671687],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002614773,"threshold_uncertainty_score":0.009386659,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0839619599965839,"score_gpt":0.298660119496544,"score_spread":0.2146981594999601,"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."}}