{"id":"W4400335180","doi":"10.3389/fneur.2024.1394210","title":"Depressive and mania mood state detection through voice as a biomarker using machine learning","year":2024,"lang":"en","type":"article","venue":"Frontiers in Neurology","topic":"Emotion and Mood Recognition","field":"Psychology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Beijing Municipal Science and Technology Commission","keywords":"Mood; Mania; Linear discriminant analysis; Psychology; Bipolar disorder; Major depressive disorder; Artificial intelligence; Computer science; Cognitive psychology; Speech recognition; Clinical psychology","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":[0.001038537,0.0005693989,0.0005410523,0.0007760985,0.0001557603,0.0008494022,0.0002404883,0.0004611115,0.001177425],"category_scores_gemma":[0.002172428,0.0001114259,0.0003734225,0.0004161423,0.0002580829,0.0003331809,0.0003719204,0.0002707679,0.0005351066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001764767,"about_ca_system_score_gemma":0.0002556464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006459625,"about_ca_topic_score_gemma":0.001219799,"domain_scores_codex":[0.9996619,0.0001015585,0.00003916345,0.00008237757,0.00008047474,0.0000345051],"domain_scores_gemma":[0.9992669,0.0003282512,0.0001735031,0.00004582234,0.0001405455,0.00004489056],"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":[0.001878405,0.0002774672,0.3824046,0.0008872846,0.0004914208,0.0005838377,0.0005363009,0.004821611,0.1504674,0.0004987374,0.0022732,0.4548796],"study_design_scores_gemma":[0.00008789019,0.00149379,0.8598632,0.0002518482,0.0005059364,0.002414078,0.0005799823,0.07957778,0.04954172,0.002105902,0.003450685,0.000127164],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9464194,0.003228932,0.04510393,0.0003388832,0.0001512453,0.0002123356,0.001245458,0.0003524784,0.002947243],"genre_scores_gemma":[0.9844135,0.0007487261,0.01323152,0.0001308285,0.00008943683,0.00008599325,0.0005808072,0.00001595857,0.0007031491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001177425,"threshold_uncertainty_score":0.005492389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02207658176792283,"score_gpt":0.2980893256990676,"score_spread":0.2760127439311448,"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."}}