{"id":"W4410992039","doi":"10.1364/ofc.2025.tu2f.5","title":"Impact of Line-side and Client-side Errors Using Iterative and Non-Iterative Decoding for Concatenated KP4-BCH FEC","year":2025,"lang":"en","type":"article","venue":"","topic":"Advancements in Photolithography Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Infineon Technologies (Canada)","funders":"","keywords":"BCH code; Decoding methods; Computer science; Line (geometry); Algorithm; Mathematics","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":[0.0001327927,0.0002376515,0.0003601262,0.0003084018,0.00008327419,0.00004558767,0.000070815,0.00008533541,0.00000616737],"category_scores_gemma":[0.00005425744,0.000204959,0.00008221161,0.0002924994,0.0000999462,0.0002841284,0.00005718582,0.0001107717,9.572466e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009166985,"about_ca_system_score_gemma":0.00002072321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005244568,"about_ca_topic_score_gemma":0.00001732664,"domain_scores_codex":[0.9990487,0.00002091479,0.0003677419,0.0002402204,0.00006702752,0.0002554341],"domain_scores_gemma":[0.9994067,0.0002006774,0.00007260503,0.0001434986,0.0001183418,0.00005819867],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003500332,0.0001455192,0.1256808,0.001066439,0.001937638,0.00001516183,0.00467525,0.01429029,0.8244492,0.005545447,0.0005346957,0.0213095],"study_design_scores_gemma":[0.001412891,0.0003207639,0.008849015,0.0004711613,0.00009752104,0.000006161155,0.0003522816,0.534519,0.4505566,0.002929183,0.00006282097,0.0004225835],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6935911,0.0002227787,0.3041691,0.000005148394,0.00006083851,0.0005568917,0.00005008388,0.0001312623,0.001212831],"genre_scores_gemma":[0.9092076,0.00008027299,0.0905417,0.00002816416,0.0000100623,0.00004954098,0.0000116739,0.00002413098,0.00004689111],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5202287,"threshold_uncertainty_score":0.8357983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01848696226775569,"score_gpt":0.3461553761388241,"score_spread":0.3276684138710684,"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."}}