{"id":"W2110694272","doi":"10.1109/ccece.1998.685553","title":"On the analysis and design of variable rate trellis source codes","year":2002,"lang":"en","type":"article","venue":"","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Algorithm; Rate–distortion theory; Mathematics; Trellis (graph); Decoding methods; Coding gain; Lossy compression; Computer science; Data compression; 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":[0.0002970346,0.0000556545,0.000102239,0.00006009457,0.00008511396,0.00006993143,0.0003317188,0.00001885539,0.0002111885],"category_scores_gemma":[0.00002456706,0.00002949508,0.00002311347,0.000396323,0.00002252039,0.0001266456,0.0001165579,0.00003791956,0.00001140144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000002979079,"about_ca_system_score_gemma":0.000003165199,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001564556,"about_ca_topic_score_gemma":0.000002053393,"domain_scores_codex":[0.9994592,0.00009724633,0.00009264816,0.0001616163,0.0001034052,0.00008587194],"domain_scores_gemma":[0.9990383,0.0004704355,0.00004277982,0.0003971181,0.00002302612,0.00002836313],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002958292,0.000565084,0.000953585,0.00002039419,0.0008123402,0.000009286726,0.002972802,0.1736836,0.007083854,0.5603628,0.06432382,0.1891829],"study_design_scores_gemma":[0.0000590359,0.00003429778,0.000250639,0.000003920173,0.00002380045,5.282296e-7,0.000008764559,0.9944839,0.001389248,0.003007576,0.0006926858,0.0000455546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001823198,0.00005695239,0.9963066,0.0002302668,0.00001453698,0.00004652044,0.000001875602,0.00002487783,0.001495155],"genre_scores_gemma":[0.7111525,0.0001305566,0.2833417,0.0006403137,0.00001791905,0.000006601474,0.000001753302,0.000005193747,0.004703441],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8208004,"threshold_uncertainty_score":0.2312366,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02611606809782869,"score_gpt":0.211404816436749,"score_spread":0.1852887483389203,"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."}}