{"id":"W4406458596","doi":"10.1109/jlt.2025.3530858","title":"Performance-Complexity-Latency Trade-Offs of Concatenated RS-SDBCH Codes","year":2025,"lang":"en","type":"article","venue":"Journal of Lightwave Technology","topic":"Embedded Systems Design Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Concatenated error correction code; Turbo code; Serial concatenated convolutional codes; Latency (audio); Electronic engineering; Computer network; Decoding methods; Telecommunications; Block code; Engineering","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":[0.0009467644,0.0002384637,0.0008262723,0.001887323,0.00009568987,0.00003731627,0.002349763,0.0004270271,0.00001277508],"category_scores_gemma":[0.0001448311,0.000191895,0.00017861,0.001840544,0.0003749895,0.000447534,0.000286924,0.0006646937,0.000007178026],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001529825,"about_ca_system_score_gemma":0.0002726761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007566563,"about_ca_topic_score_gemma":0.00000294382,"domain_scores_codex":[0.9974601,0.0001309124,0.001383743,0.0002777259,0.0003695995,0.0003779137],"domain_scores_gemma":[0.9975057,0.0001392189,0.001095363,0.0007464093,0.0004488215,0.00006449244],"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":[0.00008873593,0.0004719047,0.02412461,0.0003993824,0.0004960765,0.0002488478,0.0007814107,0.00001562197,0.3094424,0.6127791,0.01242221,0.03872966],"study_design_scores_gemma":[0.001015562,0.001354598,0.004867546,0.0006914211,0.00005610961,0.0009945934,0.0001120113,0.004376795,0.8948821,0.08564359,0.00569486,0.0003107834],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6582152,0.002269826,0.3069238,0.01413695,0.001458171,0.0006439181,0.000005671021,0.001058346,0.01528814],"genre_scores_gemma":[0.9416497,0.0001794441,0.05781455,0.0001128461,0.0000346154,0.000007248457,4.356438e-7,0.00001174264,0.000189453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5854397,"threshold_uncertainty_score":0.7825251,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02207860186792296,"score_gpt":0.2739603037148255,"score_spread":0.2518817018469026,"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."}}