{"id":"W2056164141","doi":"10.1007/s11277-008-9534-x","title":"Successively Structured Gaussian Two-terminal Source Coding","year":2008,"lang":"en","type":"article","venue":"Wireless Personal Communications","topic":"Wireless Communication Security Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University; Queen's University","funders":"","keywords":"Computer science; Decoding methods; Encoder; Coding (social sciences); Distributed source coding; Algorithm; Variable-length code; Source code; Shannon–Fano coding; Rate–distortion theory; Gaussian; Context-adaptive binary arithmetic coding; Theoretical computer science; Coding tree unit; Mathematics; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001703765,0.0003101202,0.0003347248,0.0002280512,0.0009770251,0.00007534333,0.002284946,0.0001475371,0.0001064634],"category_scores_gemma":[0.00002529782,0.0003533638,0.0001421127,0.0004555872,0.0005883709,0.0003719354,0.0004770073,0.0008533403,0.00006259575],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001848512,"about_ca_system_score_gemma":0.0000751209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001365085,"about_ca_topic_score_gemma":0.0002451165,"domain_scores_codex":[0.998399,0.0001825225,0.0004498479,0.00023793,0.0003383568,0.0003923762],"domain_scores_gemma":[0.9972219,0.0002418885,0.0001177566,0.00209545,0.0001495078,0.0001735042],"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":[0.0002084093,0.001833086,0.06674386,0.0009691078,0.001649767,0.0002427068,0.1522028,0.004379964,0.2259199,0.2374326,0.04073866,0.2676791],"study_design_scores_gemma":[0.00275825,0.0001209722,0.04047279,0.0006049082,0.0001545403,0.001960606,0.004057226,0.7890813,0.02828479,0.001519887,0.1276956,0.003289115],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.944087,0.002103751,0.02348226,0.001804475,0.0001523365,0.0005384032,0.0001107979,0.003400309,0.0243207],"genre_scores_gemma":[0.9874815,0.001857826,0.009870715,0.0001346873,0.00007179243,0.0001464435,0.0001538663,0.00008859981,0.0001945443],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7847013,"threshold_uncertainty_score":0.9998918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03396039112253684,"score_gpt":0.2789937649306184,"score_spread":0.2450333738080815,"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."}}