{"id":"W1521144119","doi":"10.5772/8529","title":"New Trends in Biologically-Inspired Audio Coding","year":2010,"lang":"en","type":"book-chapter","venue":"Signal Processing","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"Computer science; Speech coding; Speech recognition; Codebook; Auditory masking; Coding (social sciences); Audio signal; Lossless compression; Neural coding; Masking (illustration); Data compression; Artificial intelligence; 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":[0.0002970854,0.0005885373,0.0004940022,0.0008778237,0.0003029272,0.001701002,0.0009988814,0.001132746,0.008762054],"category_scores_gemma":[0.0006609408,0.000351043,0.0004576892,0.001081616,0.001216955,0.002193949,0.0006878656,0.00210457,0.004035925],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008310427,"about_ca_system_score_gemma":0.0003554108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004257147,"about_ca_topic_score_gemma":0.0005424902,"domain_scores_codex":[0.9998289,0.00001991237,0.000009444361,0.00003310482,0.00009774597,0.00001090135],"domain_scores_gemma":[0.9997213,0.0001571584,0.00001067463,0.00002949471,0.00006442361,0.00001679446],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004528579,0.00005545114,0.0001659287,0.00135972,0.0000397004,0.0001386425,0.0003607051,0.01048583,0.02508559,0.4266434,0.03539227,0.5002275],"study_design_scores_gemma":[0.00001524417,0.00007864441,0.0002748884,0.0002956747,0.00001775838,0.0006238245,0.00009839904,0.02933402,0.009272355,0.1852689,0.7746652,0.00005495954],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008041806,0.2440284,0.5476985,0.005479597,0.003921601,0.0000696346,0.0002172495,0.001358519,0.1891847],"genre_scores_gemma":[0.09725214,0.2355687,0.4291765,0.002785573,0.003703428,0.0002700711,0.0007657279,0.001033315,0.2294446],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008762054,"threshold_uncertainty_score":0.02931201,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03561951384583587,"score_gpt":0.2800878518970018,"score_spread":0.2444683380511659,"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."}}