{"id":"W1504604993","doi":"10.1109/isit.1993.748411","title":"A New Remainder Based Decoding Algorithm for Reed-Solomon Codes","year":2005,"lang":"en","type":"article","venue":"","topic":"Coding theory and cryptography","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Remainder; Berlekamp–Welch algorithm; Algorithm; Polynomial; Polynomial code; Decoding methods; Euclidean algorithm; Computation; List decoding; Computer science; Chinese remainder theorem; Mathematics; Sequential decoding; Arithmetic; Concatenated error correction code; Block code","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":[0.0005806761,0.0007117263,0.0006610911,0.0009287997,0.000472882,0.0009957834,0.001035453,0.0008548342,0.003385807],"category_scores_gemma":[0.00163478,0.0003306904,0.0006003407,0.0006943409,0.0005110289,0.001807167,0.0008928938,0.001095284,0.003119841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005728531,"about_ca_system_score_gemma":0.0009323317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006333463,"about_ca_topic_score_gemma":0.0009825999,"domain_scores_codex":[0.9992595,0.0001150487,0.0000637756,0.0001347649,0.0003809423,0.00004592025],"domain_scores_gemma":[0.999553,0.0001210885,0.00003879076,0.00009473618,0.0001746864,0.00001758252],"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":[0.0003001682,0.00009456577,0.0004661069,0.0002712994,0.00005932862,0.0004878841,0.0002715481,0.06792904,0.07612704,0.1869751,0.00748106,0.6595368],"study_design_scores_gemma":[0.0001292215,0.000339028,0.0003476115,0.00008465177,0.00006445005,0.00176758,0.00004787001,0.758008,0.07801031,0.07671382,0.08436146,0.0001260072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003489644,0.0002165433,0.9925882,0.0001200093,0.0001169209,0.00007329586,0.00006123718,0.0008491019,0.002484959],"genre_scores_gemma":[0.04072161,0.0004202272,0.9487067,0.000125398,0.0001295397,0.000110911,0.0002873418,0.000191422,0.009306742],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003385807,"threshold_uncertainty_score":0.01132667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01713977745125817,"score_gpt":0.256591572027516,"score_spread":0.2394517945762578,"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."}}