{"id":"W4407570587","doi":"10.1038/s41746-025-01500-w","title":"Identifying major depressive disorder in older adults through naturalistic driving behaviors and machine learning","year":2025,"lang":"en","type":"article","venue":"npj Digital Medicine","topic":"Older Adults Driving Studies","field":"Health Professions","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Calgary","funders":"National Institute on Aging; National Institutes of Health","keywords":"Naturalistic observation; Depression (economics); Logistic regression; Demographics; Population; Poison control; Gerontology; Psychology; Medicine; Demography; Medical emergency; Environmental health","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":[0.001161748,0.0002221411,0.0002259657,0.0007104923,0.000212618,0.0004154395,0.0002048709,0.000217114,0.0004230104],"category_scores_gemma":[0.005650583,0.0001143272,0.0004174881,0.0003846149,0.0001708632,0.0002804641,0.0002961872,0.0002458603,0.0001844151],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002958352,"about_ca_system_score_gemma":0.0003948736,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01417358,"about_ca_topic_score_gemma":0.0302673,"domain_scores_codex":[0.9995642,0.0002383896,0.00004809059,0.00007244897,0.00005123242,0.00002550557],"domain_scores_gemma":[0.9986451,0.0005986614,0.0003620875,0.0001354296,0.0002001222,0.00005849678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001086258,0.0001753566,0.9792399,0.00003006292,0.0001202052,0.000043832,0.0001753773,0.002121398,0.0004566633,0.0000731518,0.0003237147,0.0171317],"study_design_scores_gemma":[0.00001462147,0.0003515311,0.9635588,0.00002521718,0.00003844526,0.0002094644,0.0003906328,0.03394299,0.0004694084,0.0003706293,0.0006175411,0.00001072103],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972796,0.00007992711,0.001709121,0.00008981649,0.000004069006,0.00004882554,0.0004239935,0.00001509597,0.0003496202],"genre_scores_gemma":[0.9968855,0.00005831785,0.002276133,0.00004492552,0.000004488018,0.00002627178,0.0005740485,0.000001317903,0.0001289308],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01417358,"threshold_uncertainty_score":0.02818215,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02386728969677071,"score_gpt":0.38041774277749,"score_spread":0.3565504530807193,"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."}}