{"id":"W2105321571","doi":"10.1109/jlt.2003.808762","title":"Application of parallel forward-error correction in two-dimensional optical-data links","year":2003,"lang":"en","type":"article","venue":"Journal of Lightwave Technology","topic":"Optical Network Technologies","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Forward error correction; Computer science; Error detection and correction; Chip; Application-specific integrated circuit; Throughput; Electronic engineering; Optical communication; Fault tolerance; Optical performance monitoring; Bit error rate; Computer hardware; Wavelength-division multiplexing; Decoding methods; Optics; Telecommunications; Algorithm; Engineering; Physics","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":[0.00042023,0.0001534897,0.0004156721,0.0006683628,0.00001959818,0.000006241627,0.0005224692,0.000502773,0.00001316849],"category_scores_gemma":[0.000494644,0.0001362735,0.00005727588,0.000759418,0.0001606399,0.0001582195,0.0001010611,0.001070277,0.00001372365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001016608,"about_ca_system_score_gemma":0.00003386389,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001720115,"about_ca_topic_score_gemma":0.00001980902,"domain_scores_codex":[0.9985822,0.00001974708,0.0007594159,0.0001709066,0.0001993069,0.0002684642],"domain_scores_gemma":[0.9989244,0.0001420137,0.0002159496,0.0005293926,0.0001442653,0.00004396809],"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":[0.0002264672,0.0009570399,0.0322268,0.0001757632,0.0004969253,0.0002188946,0.00009093912,0.4993906,0.09055093,0.2045098,0.01115425,0.1600015],"study_design_scores_gemma":[0.004355195,0.001064117,0.004081397,0.0003999363,0.0001881926,0.001891513,0.0004332235,0.7281957,0.1473994,0.09107733,0.02000871,0.0009052819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8676974,0.002004806,0.12334,0.002057211,0.001305903,0.000396922,0.000006315504,0.0005843444,0.002607063],"genre_scores_gemma":[0.8950208,0.00007886048,0.1048063,0.00001375646,0.00003585609,0.000006792318,0.000002825492,0.00002135417,0.00001349205],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.228805,"threshold_uncertainty_score":0.5557073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01500693292523434,"score_gpt":0.2675623013225036,"score_spread":0.2525553683972693,"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."}}