{"id":"W2157055070","doi":"10.1002/ett.1523","title":"Collaborative algebraic decoding of interleaved Reed–Solomon codes","year":2011,"lang":"en","type":"article","venue":"Transactions on Emerging Telecommunications Technologies","topic":"Coding theory and cryptography","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"List decoding; Concatenated error correction code; Reed–Solomon error correction; Serial concatenated convolutional codes; Sequential decoding; Berlekamp–Welch algorithm; Decoding methods; Linear code; Algorithm; Mathematics; Block code; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000358883,0.0001809768,0.0002407819,0.0008190595,0.0005259573,0.0000360091,0.002604932,0.0001314831,0.00004097565],"category_scores_gemma":[0.00007365008,0.0001875805,0.0001308532,0.002169894,0.0004356883,0.0004050102,0.00008841157,0.0004122419,0.00001686779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003735611,"about_ca_system_score_gemma":0.00004093254,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000337206,"about_ca_topic_score_gemma":0.00008633728,"domain_scores_codex":[0.9987706,0.000153321,0.0003947595,0.000301196,0.0001325294,0.0002475777],"domain_scores_gemma":[0.9972217,0.0003033346,0.0002013223,0.002073898,0.0001724196,0.00002734468],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004547779,0.0006512389,0.0001682221,0.00002064388,0.0002025222,0.000001604412,0.008866527,0.0001642819,0.004063419,0.5023971,0.00008128586,0.4833377],"study_design_scores_gemma":[0.0008726591,0.001249048,0.001274701,0.000377731,0.0001215081,0.00002476246,0.0231356,0.01145114,0.6419079,0.316338,0.002153719,0.001093206],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02159732,0.0003322086,0.9695725,0.001286656,0.000104514,0.0002260695,0.000009260117,0.002252238,0.004619182],"genre_scores_gemma":[0.7500405,0.0005308984,0.2492858,0.00002327706,0.000001150929,0.00008867909,0.0000014308,0.000009771854,0.0000185105],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7284432,"threshold_uncertainty_score":0.7649311,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02428618657381141,"score_gpt":0.2586574155446826,"score_spread":0.2343712289708712,"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."}}