{"id":"W3194206822","doi":"","title":"Implementasi Algoritma Deep Artificial Neural Network Menggunakan Mel Frequency Cepstrum Coefficient Untuk Klasifikasi Audio Emosi Manusia","year":2021,"lang":"id","type":"article","venue":"","topic":"Computer Science and Engineering","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Speech recognition; Art; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005556134,0.001020914,0.0006832532,0.0004349743,0.0003790206,0.0008945572,0.00104866,0.0007000983,0.005614291],"category_scores_gemma":[0.001030019,0.0003460577,0.0006464435,0.0003552784,0.0001841765,0.0008365374,0.0004967218,0.0008955789,0.001701578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005431561,"about_ca_system_score_gemma":0.0009837174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01372594,"about_ca_topic_score_gemma":0.01308567,"domain_scores_codex":[0.9997503,0.00003296153,0.00001888282,0.00007185015,0.00007997917,0.00004605695],"domain_scores_gemma":[0.99978,0.00005002187,0.00001190014,0.00002251826,0.0001222043,0.00001343891],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005449686,0.0002162029,0.002972936,0.0003016304,0.0001916785,0.0002685044,0.00015649,0.149699,0.04649378,0.001951701,0.01307999,0.7841231],"study_design_scores_gemma":[0.00003518937,0.0001144888,0.001647738,0.00002923718,0.00006239134,0.00009201209,0.00005313173,0.9711893,0.0198012,0.0009043349,0.006043653,0.00002727904],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1325581,0.003748429,0.8358234,0.001054268,0.0008629105,0.0003009642,0.001289575,0.00896622,0.01539609],"genre_scores_gemma":[0.6938843,0.001730776,0.2764306,0.0003661721,0.0001192415,0.0003801136,0.002135656,0.0002834985,0.02466962],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01372594,"threshold_uncertainty_score":0.02729207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02064950076568246,"score_gpt":0.243752419473749,"score_spread":0.2231029187080666,"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."}}