{"id":"W7116769002","doi":"10.1038/s41467-025-66784-8","title":"Latent brain subtypes of chronotype reveal unique behavioral and health profiles across population cohorts","year":2025,"lang":"en","type":"article","venue":"Nature Communications","topic":"Circadian rhythm and melatonin","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Neurological Institute and Hospital; Mila - Quebec Artificial Intelligence Institute; Centre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal; Douglas Mental Health University Institute; McGill University; Canadian Sleep & Circadian Network","funders":"National Institute on Drug Abuse; National Institute on Aging; National Institute of Mental Health; China Scholarship Council","keywords":"Chronotype; Biobank; Trait; Population; Cohort; Population health; Profiling (computer programming)","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":[0.0007007465,0.0002395646,0.0002573747,0.0004954386,0.0002579961,0.0006499577,0.0002815679,0.0002958485,0.001881417],"category_scores_gemma":[0.002966993,0.0001336777,0.0004143507,0.000449038,0.0003080345,0.0002768053,0.0005930738,0.0004540445,0.0002628326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002178645,"about_ca_system_score_gemma":0.0002571229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006530668,"about_ca_topic_score_gemma":0.01503052,"domain_scores_codex":[0.9997734,0.00006486468,0.0000107933,0.0001036895,0.00001548789,0.00003170019],"domain_scores_gemma":[0.9992262,0.0002361955,0.0002387396,0.0001771124,0.00005627791,0.00006551147],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005513075,0.00003029688,0.9726231,0.00003807405,0.0003597396,0.00008374001,0.0004180422,0.0009958888,0.003731899,0.0006283077,0.001049528,0.01949007],"study_design_scores_gemma":[0.00001280428,0.00006037995,0.9939538,0.0000191592,0.00007013882,0.0001760373,0.0001993128,0.003064436,0.0004433459,0.001277354,0.0007121876,0.00001099816],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939977,0.0002310639,0.003525109,0.0001308393,0.000008646115,0.00000923374,0.00156273,0.00003853645,0.0004960837],"genre_scores_gemma":[0.9968228,0.00009758294,0.001369281,0.0000353107,0.000007262922,0.00001750632,0.001311291,0.00001330795,0.0003256232],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006530668,"threshold_uncertainty_score":0.01298535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04365884441887051,"score_gpt":0.3853844578871348,"score_spread":0.3417256134682642,"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."}}