{"id":"W1995345730","doi":"10.1109/tcomm.2014.2367014","title":"Flexible Symmetric Multiple Description Lattice Vector Quantizer With &lt;inline-formula&gt; &lt;tex-math notation=\"TeX\"&gt;$L\\geq 3$&lt;/tex-math&gt;&lt;/inline-formula&gt; Descriptions","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Mathematics; Decoding methods; Lattice (music); Algorithm; Erasure; Notation; Discrete mathematics; Arithmetic; Computer science","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","sts","open_science"],"consensus_categories":[],"category_scores_codex":[0.001310423,0.001145944,0.001056688,0.001942119,0.003241014,0.0008392943,0.005750889,0.0005464908,0.00006131669],"category_scores_gemma":[0.0003539474,0.001093344,0.0005173173,0.0048109,0.0006159079,0.004730111,0.0002371969,0.001600336,0.000674467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007193116,"about_ca_system_score_gemma":0.0004605941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001840125,"about_ca_topic_score_gemma":0.001623314,"domain_scores_codex":[0.9927831,0.0008511592,0.00190563,0.001623529,0.001532952,0.001303666],"domain_scores_gemma":[0.9858192,0.002251033,0.000965277,0.008780629,0.00153635,0.0006475523],"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":[0.0003914886,0.008057734,0.0001609593,0.0003626889,0.000724586,0.00001786728,0.003345729,0.04241297,0.1360714,0.6724023,0.004647618,0.1314047],"study_design_scores_gemma":[0.002837633,0.0008479338,0.001641958,0.000694098,0.0003803232,0.000142716,0.00009949595,0.8348776,0.02230709,0.004445377,0.129846,0.001879791],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01278646,0.0007566419,0.9759343,0.002443212,0.0009229304,0.001909831,0.0005364189,0.003147376,0.001562857],"genre_scores_gemma":[0.6201811,0.001241979,0.3754736,0.0004488842,0.00009238593,0.0009478124,0.0003123651,0.0001437982,0.001157975],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7924646,"threshold_uncertainty_score":0.9996285,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04422991991100132,"score_gpt":0.2856313339258765,"score_spread":0.2414014140148752,"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."}}