{"id":"W7056460801","doi":"","title":"Ethnic recognition system for Malay language speakers using gammatone frequency cepstral coefficients pitch (GFCCP) and pattern classification","year":2022,"lang":"en","type":"other","venue":"UTHM Institutional Repository (Universiti Tun Hussein Onn Malaysia)","topic":"Magnetic confinement fusion research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"auDA Foundation; Garron Family Cancer Centre; Universiti Tun Hussein Onn Malaysia","keywords":"Malay; Mel-frequency cepstrum; Feature (linguistics); Cepstrum; Support vector machine; Feature extraction; Pattern recognition (psychology)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003970019,0.0006500116,0.00053586,0.001083165,0.000392579,0.0006143235,0.0004885014,0.0004513446,0.004183763],"category_scores_gemma":[0.001137386,0.0001378809,0.0004810425,0.0004118232,0.0001154994,0.0006482843,0.0005190097,0.0004250967,0.004186913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002779043,"about_ca_system_score_gemma":0.0004345296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005146035,"about_ca_topic_score_gemma":0.005235736,"domain_scores_codex":[0.9996262,0.00003522999,0.00004575569,0.000124039,0.000118781,0.00004996764],"domain_scores_gemma":[0.9995184,0.00005754966,0.00004546288,0.00004569639,0.0002966237,0.00003629265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0008427258,0.000323311,0.01909269,0.0003725389,0.0001244742,0.001603756,0.0005051272,0.004209178,0.1722113,0.0008178112,0.01945012,0.780447],"study_design_scores_gemma":[0.0001411396,0.000947571,0.1718164,0.0001733795,0.0002960317,0.003922222,0.001840943,0.5518969,0.2298125,0.002032242,0.03682735,0.0002934168],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6370857,0.001014928,0.3054767,0.0006565191,0.0007040628,0.001101546,0.008395643,0.01852349,0.02704144],"genre_scores_gemma":[0.7731447,0.0005978767,0.1884468,0.0001903658,0.0001108439,0.0005962633,0.0118498,0.0002970693,0.02476632],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005146035,"threshold_uncertainty_score":0.01399612,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03100944210997712,"score_gpt":0.2653325719179715,"score_spread":0.2343231298079944,"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."}}