{"id":"W4413228311","doi":"10.51401/jinteks.v7i2.5886","title":"METODE MFCC-SVM UNTUK PENGENALAN TINGKAT EMOSI MANUSIA BERDASARKAN BERAGAM DATASET","year":2025,"lang":"id","type":"article","venue":"Jurnal Informatika Teknologi dan Sains (Jinteks)","topic":"Data Mining and Machine Learning Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Humanities; Physics; Art","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","scholarly_communication","open_science","research_integrity","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002034755,0.001109887,0.001174405,0.001248988,0.001624262,0.00221459,0.006072403,0.0005917784,0.0002048805],"category_scores_gemma":[0.0009805439,0.001035238,0.0004040275,0.002175026,0.0005644384,0.002641625,0.00418186,0.002919155,0.00266969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005079549,"about_ca_system_score_gemma":0.0008382211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006859582,"about_ca_topic_score_gemma":0.0003707852,"domain_scores_codex":[0.9932714,0.0004738658,0.002285944,0.00128582,0.0009455128,0.001737489],"domain_scores_gemma":[0.9932808,0.0006771027,0.001343083,0.003733956,0.0004041188,0.0005609191],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001094725,0.0006612829,0.005419887,0.0005204345,0.0008532621,0.0001483442,0.004977498,0.0007565554,0.000344347,0.03460372,0.6697379,0.2818672],"study_design_scores_gemma":[0.001369548,0.0004084998,0.01271388,0.000605954,0.0002498434,0.0004293725,0.001298785,0.05582667,0.000942065,0.0003787992,0.924619,0.001157562],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2066948,0.003665973,0.4149798,0.04227301,0.007880067,0.005797039,0.01613597,0.004801557,0.2977718],"genre_scores_gemma":[0.8127328,0.002305218,0.08217122,0.03333279,0.001318407,0.000758032,0.02918086,0.0002771389,0.03792359],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.606038,"threshold_uncertainty_score":0.9996755,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01729348251920042,"score_gpt":0.2978298249908943,"score_spread":0.2805363424716939,"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."}}