{"id":"W2128054765","doi":"10.1109/scft.1993.762319","title":"Acelp speech coding at 8 kbit/s with a 10 ms frame: a candidate for ccitt standardization","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Data Compression Techniques","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Standardization; Computer science; Coding (social sciences); Speech coding; Speech recognition; Frame (networking); Telecommunications; 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":[0.003717653,0.0007727263,0.0006376606,0.001398365,0.001554007,0.002280967,0.001582757,0.001831055,0.008688848],"category_scores_gemma":[0.003366009,0.0001877418,0.0002893343,0.000841068,0.000935094,0.001170413,0.0009449881,0.00171326,0.004551596],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001017177,"about_ca_system_score_gemma":0.003264272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004876604,"about_ca_topic_score_gemma":0.005695423,"domain_scores_codex":[0.9987466,0.0002460481,0.0000947169,0.0001423531,0.0004189531,0.0003512143],"domain_scores_gemma":[0.9939374,0.0003472228,0.0001588587,0.0007571979,0.004088902,0.000710467],"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":[0.004117332,0.001016295,0.007049167,0.000335781,0.00008329278,0.001628582,0.0007236229,0.004910843,0.2240378,0.1023905,0.0422094,0.6114975],"study_design_scores_gemma":[0.0004111923,0.00436165,0.01197335,0.0003037171,0.0002268657,0.002145785,0.001011484,0.06154615,0.5321278,0.02222001,0.3635072,0.0001647762],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1638708,0.002223485,0.6417942,0.008571699,0.001990822,0.002008937,0.001737137,0.008437395,0.1693657],"genre_scores_gemma":[0.6192448,0.001337555,0.2821189,0.002211968,0.0009506691,0.00114097,0.006143484,0.001003303,0.08584836],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008688848,"threshold_uncertainty_score":0.02906704,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01145776885146098,"score_gpt":0.2788272810435693,"score_spread":0.2673695121921083,"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."}}