{"id":"W2009605565","doi":"10.1109/twc.2013.062413.122017","title":"Designing Optimal Multiresolution Quantizers with Error Detecting Codes","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Vector quantization; Quantization (signal processing); Computer science; Algorithm; Decoding methods; Redundancy (engineering); Coding (social sciences); Mathematics","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":[0.001388905,0.0005968516,0.0008095769,0.0004692985,0.0003020171,0.0008641149,0.0009458619,0.0007736075,0.00093298],"category_scores_gemma":[0.006162064,0.0004468369,0.0002488716,0.0005076617,0.000684126,0.001409419,0.0009368971,0.0007527682,0.0002475725],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006644989,"about_ca_system_score_gemma":0.0007498451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001205326,"about_ca_topic_score_gemma":0.001327073,"domain_scores_codex":[0.9988185,0.0003070852,0.00006718064,0.0001997767,0.0005020035,0.0001055012],"domain_scores_gemma":[0.9982426,0.0009111661,0.0003558177,0.0001468947,0.0002995763,0.00004400772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003805092,0.00008930857,0.0009518437,0.0003125886,0.00006563288,0.0001746582,0.0003189395,0.610081,0.07026352,0.100015,0.00171532,0.2156318],"study_design_scores_gemma":[0.00003113946,0.0001017599,0.00009276246,0.00002068916,0.00001170079,0.00005010745,0.00002435295,0.9814663,0.009982558,0.007044476,0.001154931,0.00001938103],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01450416,0.0003866143,0.9839787,0.00009566323,0.00002102677,0.00003524917,0.00002398531,0.00009483436,0.0008599581],"genre_scores_gemma":[0.5592665,0.0005456289,0.4386322,0.000134916,0.0000575349,0.0001122875,0.00006580399,0.00004107319,0.001144035],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001388905,"threshold_uncertainty_score":0.007345319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04497314982665732,"score_gpt":0.3006034573517701,"score_spread":0.2556303075251127,"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."}}