{"id":"W4387023042","doi":"10.2196/48210","title":"Using Wearable Devices and Speech Data for Personalized Machine Learning in Early Detection of Mental Disorders: Protocol for a Participatory Research Study","year":2023,"lang":"en","type":"article","venue":"JMIR Research Protocols","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wearable computer; Computer science; Context (archaeology); Data collection; Mental health; Mood; Machine learning; Artificial intelligence; Psychology; Clinical psychology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.05939822,0.003835594,0.005110754,0.003442175,0.008826389,0.004258676,0.002979324,0.006048018,0.05013841],"category_scores_gemma":[0.06454201,0.003980122,0.004538115,0.002955717,0.003996664,0.003604511,0.004109931,0.0100544,0.0145187],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007207956,"about_ca_system_score_gemma":0.02386028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008188793,"about_ca_topic_score_gemma":0.01205991,"domain_scores_codex":[0.9757611,0.01442531,0.003354729,0.002039484,0.002086691,0.002332731],"domain_scores_gemma":[0.9480181,0.0200845,0.003909795,0.0095932,0.0155459,0.002848606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.1258238,0.07985509,0.009671234,0.082861,0.001873386,0.005961663,0.05728576,0.01287353,0.010542,0.02943572,0.1692936,0.4145232],"study_design_scores_gemma":[0.2316596,0.07557876,0.0391486,0.04922267,0.001448185,0.0009961014,0.04666533,0.00791942,0.00881958,0.04038351,0.4962553,0.001902906],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"protocol","genre_gemma":"protocol","genre_scores_codex":[0.00215471,0.0001090639,0.002526033,0.0002130427,0.000175113,0.9929523,0.0009838311,0.00005516679,0.0008308187],"genre_scores_gemma":[0.0005735873,0.00002940963,0.0009705208,0.00004988231,0.000009235125,0.9982017,0.00004910502,0.000002427327,0.0001140334],"genre_candidate":"protocol","genre_consensus":"protocol","teacher_disagreement_score":0.05939822,"threshold_uncertainty_score":0.3141316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7784758853722034,"score_gpt":0.7051908703534142,"score_spread":0.07328501501878915,"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."}}