{"id":"W1980698970","doi":"10.1109/mcom.2006.1637952","title":"Extended AMR-WB for high-quality audio on mobile devices","year":2006,"lang":"en","type":"article","venue":"IEEE Communications Magazine","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":33,"is_retracted":false,"has_abstract":true,"ca_institutions":"VoiceAge (Canada)","funders":"Academy of Finland","keywords":"Codec; Computer science; Adaptive Multi-Rate audio codec; Sound quality; Audio over Ethernet; Bit rate; Digital audio broadcasting; Speech coding; Multimedia; Mobile device; Audio signal; Computer network; Telecommunications; Speech recognition; Digital audio; Speech processing; Voice activity detection; Operating system","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":[0.000434654,0.0002008004,0.0002559048,0.0001523604,0.0004046462,0.000124341,0.004354971,0.0000761464,0.00001280908],"category_scores_gemma":[0.00008854072,0.0001900774,0.00007243642,0.000516673,0.0001453876,0.0006291172,0.0008081734,0.0002136373,0.0001453023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008345157,"about_ca_system_score_gemma":0.00005266317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005446741,"about_ca_topic_score_gemma":0.0001146737,"domain_scores_codex":[0.9983267,0.000205581,0.0005061445,0.000436286,0.0002449486,0.0002804098],"domain_scores_gemma":[0.9926073,0.0008360909,0.0002945342,0.005873264,0.0003243991,0.00006441367],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002858666,0.001180503,0.0001095773,0.00004496718,0.00002188429,0.000001505771,0.000058342,0.0003899676,0.03282155,0.745577,0.1198133,0.09995281],"study_design_scores_gemma":[0.00105251,0.0003715959,0.01601228,0.0001280192,0.00001929344,0.000007834346,0.00001214959,0.009402582,0.07718527,0.176726,0.7183315,0.0007510417],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002123043,0.0005071432,0.9874972,0.002185859,0.0002422395,0.0008345816,0.0001206978,0.001061705,0.005427553],"genre_scores_gemma":[0.4506044,0.0001021701,0.546946,0.000426595,0.00007154086,0.0007786807,0.0001568221,0.00001830358,0.0008954963],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5985182,"threshold_uncertainty_score":0.8092691,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04279933091079921,"score_gpt":0.3562517374871472,"score_spread":0.313452406576348,"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."}}