{"id":"W2162489452","doi":"10.1142/s0219691305000853","title":"ON COARSE QUANTIZATION OF TIGHT GABOR FRAME EXPANSIONS","year":2005,"lang":"en","type":"article","venue":"International Journal of Wavelets Multiresolution and Information Processing","topic":"Mathematical Analysis and Transform Methods","field":"Mathematics","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Quantization (signal processing); Mathematics; A priori and a posteriori; Translation (biology); Gabor wavelet; Frame (networking); Fourier transform; Mathematical analysis; Algorithm; Pure mathematics; Applied mathematics; Computer science; Artificial intelligence; Wavelet","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":[0.0007105559,0.0001148541,0.0002470091,0.0004145326,0.00007800491,0.00007677434,0.0001597069,0.00007687127,0.0001106997],"category_scores_gemma":[0.0008746606,0.00008575077,0.0001073329,0.0001484229,0.00006099851,0.001955702,0.00001937526,0.0001627309,0.000006025329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005238966,"about_ca_system_score_gemma":0.00006416452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000238621,"about_ca_topic_score_gemma":0.000001815143,"domain_scores_codex":[0.9980261,0.00004896359,0.001109214,0.00006214449,0.000649236,0.0001043855],"domain_scores_gemma":[0.9975879,0.000229573,0.000961657,0.00007042493,0.001074469,0.00007596587],"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":[0.0003195937,0.0005421588,0.0001168491,0.000289756,0.0001851593,0.000002517779,0.005540105,0.001079256,0.002155414,0.3771172,0.0007080819,0.611944],"study_design_scores_gemma":[0.005477582,0.0004334628,0.002247222,0.002365747,0.0002585434,0.0002664395,0.001609978,0.8543819,0.02306557,0.08202463,0.02729164,0.0005773183],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.244435,0.0001012112,0.7500147,0.00201068,0.0002026929,0.0001315991,0.00001369141,0.00002386372,0.003066621],"genre_scores_gemma":[0.907154,0.0001075341,0.09230006,0.0002980541,0.00008860031,0.000001666872,0.000007859063,0.000006225749,0.00003605551],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8533026,"threshold_uncertainty_score":0.3496815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03373994334416891,"score_gpt":0.3597206530376091,"score_spread":0.3259807096934402,"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."}}