{"id":"W3102156549","doi":"","title":"On Optimal Zero-Delay Coding of Vector Markov Sources","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Bounded function; Markov process; Quantization (signal processing); Vector quantization; Markov chain; Encoder; Mathematical optimization; Markov decision process; Applied mathematics; Algorithm; Control theory (sociology); Computer science; Mathematical analysis; Statistics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001421005,0.0005250648,0.0006400275,0.0004379193,0.0003345658,0.0008567864,0.0006996458,0.0005374108,0.002320941],"category_scores_gemma":[0.004432873,0.0002834309,0.0003105702,0.0006944312,0.001659294,0.001301955,0.001100467,0.001037096,0.0001499985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00169584,"about_ca_system_score_gemma":0.00155443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00453076,"about_ca_topic_score_gemma":0.002329434,"domain_scores_codex":[0.9993644,0.0002423487,0.00002743146,0.00009177926,0.0001627572,0.0001113524],"domain_scores_gemma":[0.9973992,0.001948639,0.00022777,0.00008460764,0.0002798596,0.00005984813],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001654948,0.00002758021,0.0002369451,0.00006797822,0.00001319774,0.00006296078,0.00006643056,0.6990499,0.002350421,0.2827573,0.0009625671,0.01423923],"study_design_scores_gemma":[0.00001243497,0.000023832,0.00004020087,0.00001284136,0.000002850216,0.00001049203,0.000008963134,0.951951,0.0008082265,0.04678722,0.0003340874,0.000007907977],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04015318,0.0006476732,0.9528377,0.0005463971,0.00007607151,0.00003886643,0.0001276831,0.00007491035,0.005497566],"genre_scores_gemma":[0.9611626,0.0007857953,0.03412324,0.0001017615,0.00006625278,0.00006744633,0.0001243599,0.00003197271,0.003536651],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00453076,"threshold_uncertainty_score":0.01230425,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01208695500442792,"score_gpt":0.2160169058729962,"score_spread":0.2039299508685682,"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."}}