{"id":"W4396221550","doi":"10.1016/j.biopsych.2024.02.099","title":"An Longitudinal Assessment of Dimensional and Categorical Approaches to Explain Individual Differences in Depression","year":2024,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Mental Health Research Topics","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Categorical variable; Depression (economics); Psychology; Longitudinal data; Longitudinal study; Clinical psychology; Statistics; Mathematics; Computer science; Data mining; Economics","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":[0.0144927,0.0003236397,0.0002735756,0.0008446745,0.00136027,0.001162063,0.000788243,0.0006775897,0.001783055],"category_scores_gemma":[0.03336595,0.0003542509,0.0007534842,0.0007725363,0.0004939874,0.001610748,0.001030323,0.001498293,0.0003401335],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007022015,"about_ca_system_score_gemma":0.001340132,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00941992,"about_ca_topic_score_gemma":0.01231399,"domain_scores_codex":[0.99743,0.001920356,0.0001172157,0.0002009931,0.0002229515,0.0001084934],"domain_scores_gemma":[0.9800802,0.009024109,0.002695454,0.003960773,0.003371352,0.0008680424],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004573506,0.0003716056,0.9818326,0.00001587212,0.000117879,0.00002647008,0.001165077,0.0002858463,0.0004930195,0.0009490919,0.0004300525,0.01385514],"study_design_scores_gemma":[0.0000407304,0.00128508,0.9871137,0.00002961671,0.0001198352,0.0001342967,0.001555404,0.005773065,0.0004180582,0.002460743,0.001041,0.00002837735],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9929364,0.0002160047,0.004955672,0.0003687442,0.00003360833,0.0000765261,0.0006072862,0.00002930722,0.0007765361],"genre_scores_gemma":[0.9951712,0.0000684988,0.003336001,0.00005774292,0.0000113515,0.0001282859,0.0005866206,0.00000746995,0.0006328284],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0144927,"threshold_uncertainty_score":0.07664567,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4213848880174407,"score_gpt":0.4608718750130395,"score_spread":0.03948698699559883,"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."}}