{"id":"W4387096841","doi":"10.21203/rs.3.rs-3271197/v1","title":"Depressive and Mania Mood State Detection through Voice as a Biomarker Using Machine Learning","year":2023,"lang":"en","type":"preprint","venue":"Research Square","topic":"Stuttering Research and Treatment","field":"Psychology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Mania; Mood; Psychology; Bipolar disorder; Biomarker; Depression (economics); Clinical psychology; Psychiatry; Chemistry","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":[0.001259276,0.0003952258,0.0005482869,0.001161761,0.0001800361,0.0009042805,0.0002592615,0.0004254372,0.000888338],"category_scores_gemma":[0.002354708,0.0001171133,0.0004113986,0.0007100442,0.0002082402,0.0003984715,0.0003239651,0.0003241344,0.0001931931],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002897854,"about_ca_system_score_gemma":0.0002975988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001166092,"about_ca_topic_score_gemma":0.00133608,"domain_scores_codex":[0.9994453,0.0002276815,0.00007215462,0.00009704911,0.000103631,0.0000541017],"domain_scores_gemma":[0.9988048,0.0005280064,0.0002975057,0.00005314465,0.000243615,0.00007283629],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007229472,0.0002629998,0.8232648,0.0003366029,0.0002947327,0.0002109793,0.0002394225,0.003160305,0.01429652,0.0002306781,0.0009688173,0.1560111],"study_design_scores_gemma":[0.00006985365,0.001353943,0.8918314,0.000158752,0.0003995553,0.0005970591,0.0006976654,0.09186339,0.01009008,0.00111446,0.001751835,0.00007207819],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9808308,0.00214867,0.01446609,0.0003311472,0.0000789747,0.0001152893,0.0006104255,0.0001002833,0.001318367],"genre_scores_gemma":[0.9936307,0.0003353711,0.005333866,0.00006905919,0.0000519724,0.00005264449,0.0002387409,0.000002418646,0.0002852556],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001259276,"threshold_uncertainty_score":0.006659806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1750082103075906,"score_gpt":0.4803991126131102,"score_spread":0.3053909023055196,"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."}}