{"id":"W7132936615","doi":"","title":"Advancing Precision Medicine in Psychiatry: Genetic Insights into Antidepressant Treatment Outcomes","year":2025,"lang":"","type":"dissertation","venue":"TSpace","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Major depressive disorder; Escitalopram; Antidepressant; Pharmacogenetics; CYP2C19; Depression (economics); Aripiprazole; Precision medicine; Pharmacogenomics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02314504,0.001283669,0.004104343,0.003504204,0.0006300593,0.004432553,0.001516042,0.00193674,0.004002553],"category_scores_gemma":[0.04981237,0.000528655,0.003098748,0.003797877,0.001647916,0.00261105,0.002087887,0.003223704,0.0007021155],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002299699,"about_ca_system_score_gemma":0.003919782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006281288,"about_ca_topic_score_gemma":0.006996491,"domain_scores_codex":[0.9879962,0.007376922,0.0008662171,0.001774511,0.001750632,0.0002355311],"domain_scores_gemma":[0.9578337,0.0308841,0.00416238,0.00321911,0.00341791,0.0004827006],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001136433,0.0002396047,0.1059032,0.01246068,0.01928505,0.0003247898,0.0009249682,0.006165005,0.002383988,0.03825942,0.0332726,0.7796443],"study_design_scores_gemma":[0.00166796,0.002494924,0.1900726,0.02578365,0.03081976,0.001247956,0.001431545,0.02405204,0.003874844,0.4980704,0.2199505,0.0005338989],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.03157235,0.7849788,0.06962083,0.09212407,0.003495797,0.00024097,0.006687636,0.00051715,0.01076241],"genre_scores_gemma":[0.4918537,0.3843726,0.06728111,0.04038946,0.009564765,0.0005667745,0.003445724,0.0001848969,0.002341062],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02314504,"threshold_uncertainty_score":0.1224041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01081632468404584,"score_gpt":0.3490533774676424,"score_spread":0.3382370527835965,"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."}}