{"id":"W2168404597","doi":"10.1109/tsp.2005.863032","title":"Combined source and channel coding with JPEG2000 and rate-compatible low-density Parity-check codes","year":2006,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Algorithm; Low-density parity-check code; Computer science; Parity bit; Coding gain; Channel (broadcasting); Forward error correction; Decoding methods; Code rate; Bit error rate; Turbo code; Coding (social sciences); Viterbi decoder; Mathematics; Telecommunications; Statistics","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":[0.0003569686,0.0002511097,0.0002732041,0.0001993146,0.0008941442,0.0005342469,0.0002197641,0.00009130299,0.000002854642],"category_scores_gemma":[0.000002552724,0.000232768,0.0000315936,0.0004466666,0.0001880202,0.0006693414,0.000006736233,0.0003679009,0.000002325002],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004844282,"about_ca_system_score_gemma":0.0000863815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002953589,"about_ca_topic_score_gemma":0.0001673678,"domain_scores_codex":[0.9985771,0.00008809585,0.0002413363,0.0005299167,0.0002431249,0.0003204005],"domain_scores_gemma":[0.9992734,0.0001651717,0.0001299032,0.0002057651,0.0001303617,0.00009542464],"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":[0.001757033,0.003313015,0.007390935,0.002610976,0.0002631955,0.0002739967,0.01964737,0.0960473,0.2308979,0.001859452,0.0005977352,0.6353411],"study_design_scores_gemma":[0.000954479,0.0004602119,0.001325379,0.000641151,0.00004810072,0.0001236849,0.0001712658,0.5935544,0.3999733,0.002104432,0.00002712712,0.0006165397],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2542069,0.00005935688,0.7446657,0.0001707153,0.00003988265,0.0001543257,0.000001292278,0.0005734469,0.0001283592],"genre_scores_gemma":[0.9847124,0.000009317332,0.01493505,0.0001544942,0.00002432868,0.00002082789,7.446354e-7,0.00002454214,0.0001183147],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7305055,"threshold_uncertainty_score":0.9492005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01339460572769403,"score_gpt":0.2282331415684473,"score_spread":0.2148385358407533,"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."}}