{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005955728,0.0005387684,0.0003773286,0.0009935986,0.0002536775,0.0004671194,0.0005982461,0.0004867922,0.001473354],"category_scores_gemma":[0.001608073,0.0002075151,0.0002904171,0.0009209356,0.0004153403,0.0005972699,0.0007338295,0.0005793496,0.0006207497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003428487,"about_ca_system_score_gemma":0.0006757035,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001395415,"about_ca_topic_score_gemma":0.002645514,"domain_scores_codex":[0.9994704,0.00008524043,0.00002201298,0.00004726127,0.0003302956,0.00004477421],"domain_scores_gemma":[0.999323,0.0001436413,0.00007072271,0.0001301948,0.0002968413,0.00003552907],"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":[0.001626214,0.0002808845,0.002639571,0.0004115671,0.0001538241,0.0004827385,0.0001947193,0.1132919,0.3592064,0.02680192,0.004147443,0.4907628],"study_design_scores_gemma":[0.0001850898,0.0004286714,0.001651566,0.00004976729,0.00009873669,0.0007948377,0.00003978449,0.6638751,0.3207476,0.004504323,0.007551499,0.00007302221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1194655,0.0009324013,0.8715252,0.0001785368,0.0001042164,0.000264064,0.0002105306,0.001699212,0.005620314],"genre_scores_gemma":[0.6480391,0.0004786552,0.3441311,0.00008832286,0.00007043641,0.0001840262,0.0003738426,0.00008484067,0.006549492],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001473354,"threshold_uncertainty_score":0.004928887,"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."}}