{"id":"W2975353307","doi":"10.1109/isit.2019.8849456","title":"Improved Soft Decoding of Reed-Solomon Codes on Gilbert-Elliott Channels","year":2019,"lang":"en","type":"article","venue":"","topic":"Coding theory and cryptography","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"List decoding; Decoding methods; Reed–Solomon error correction; Sequential decoding; Algorithm; Berlekamp–Welch algorithm; Concatenated error correction code; Computer science; Block code; Theoretical 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001527327,0.0007152751,0.0005520957,0.0009964254,0.000460639,0.0009838588,0.0007036381,0.0006676469,0.0006923846],"category_scores_gemma":[0.008564049,0.000295082,0.0003227308,0.0007419289,0.001229945,0.001203321,0.001159947,0.0007641292,0.0002295619],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001226873,"about_ca_system_score_gemma":0.001389907,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002155111,"about_ca_topic_score_gemma":0.002085268,"domain_scores_codex":[0.9986284,0.0006146309,0.00006205722,0.00008937161,0.0004215471,0.0001840374],"domain_scores_gemma":[0.9941146,0.004133706,0.0004625591,0.0005707948,0.0005859681,0.0001324464],"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":[0.0008786889,0.00007257928,0.0020188,0.0001420825,0.00005351844,0.0003047748,0.0003878105,0.825077,0.03071636,0.09475702,0.0006261342,0.04496526],"study_design_scores_gemma":[0.0000436573,0.0001200218,0.0002524941,0.00001648421,0.00001673598,0.00006277856,0.00002746508,0.9585078,0.02400694,0.01648331,0.0004366245,0.00002579975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4507911,0.0004260428,0.5425777,0.0003510151,0.00005725965,0.00008549989,0.0001010271,0.0007785563,0.004831742],"genre_scores_gemma":[0.9392606,0.0002033754,0.05908664,0.00007023862,0.00001860184,0.00003390712,0.00004153931,0.00002458268,0.001260497],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002155111,"threshold_uncertainty_score":0.008901596,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01193483900419957,"score_gpt":0.2293324753635101,"score_spread":0.2173976363593106,"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."}}