{"id":"W1556738854","doi":"","title":"Processing of Speech and Non-Speech Tonal Information by Native and Nonnative Tone Language Speakers: an Event-Related Electrophysiological Study","year":2010,"lang":"en","type":"article","venue":"Canadian acoustics","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Tone (literature); Speech recognition; Computer science; Event (particle physics); Speech processing; Linguistics; Physics; Astrophysics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001013732,0.00009492498,0.0001128129,0.00007179632,0.0001322396,0.00009178479,0.0001958067,0.00006459344,0.000006247667],"category_scores_gemma":[0.00002608699,0.00008376724,0.000009258471,0.0002653523,0.000085728,0.0004202088,0.00004345612,0.0002279902,0.000001475271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002647133,"about_ca_system_score_gemma":0.0001260589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001783454,"about_ca_topic_score_gemma":0.002052811,"domain_scores_codex":[0.9993578,0.00001828738,0.000164226,0.0001659889,0.0001103935,0.0001833563],"domain_scores_gemma":[0.9994142,0.0000316829,0.00008767204,0.0001413068,0.000123603,0.0002015381],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002059875,0.0002519493,0.001002773,0.00004326914,0.00005451516,0.00005170824,0.01617776,0.0004124821,0.5041589,0.00313693,0.001590166,0.473099],"study_design_scores_gemma":[0.001495816,0.001838148,0.1591343,0.0000444935,0.00005943446,0.0000999285,0.005243707,0.8205907,0.007894048,0.002345276,0.000447165,0.0008069833],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98698,0.00002601892,0.01229417,0.0001702678,0.00003796331,0.0002870309,0.00002992162,0.00001795616,0.0001566439],"genre_scores_gemma":[0.99583,0.000006294135,0.003928384,0.0001470638,0.00003286549,0.000007825723,0.00001910771,0.000003817857,0.00002465771],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8201783,"threshold_uncertainty_score":0.3415929,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004696560725624769,"score_gpt":0.2521741476048757,"score_spread":0.2474775868792509,"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."}}