{"id":"W4408406293","doi":"10.1177/07067437251322399","title":"Personalising Antidepressant Treatment for Unipolar Depression Combining Individual Choices, Risks and big Data: The PETRUSHKA Tool: Personnalisation du traitement antidépresseur de la dépression unipolaire associant choix individuels, risques et mégadonnées: l’outil PETRUSHKA","year":2025,"lang":"en","type":"article","venue":"The Canadian Journal of Psychiatry","topic":"Digital Mental Health Interventions","field":"Psychology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Centre for Addiction and Mental Health","funders":"National Institute for Health and Care Research; Wellcome Trust","keywords":"Bespoke; Randomized controlled trial; Depression (economics); Medicine; Psychiatry; Psychology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.01584962,0.001018118,0.001325337,0.002302713,0.0006124268,0.003594156,0.001855331,0.001448344,0.01543663],"category_scores_gemma":[0.0928382,0.0006833503,0.001870273,0.002053519,0.0005594176,0.002862712,0.003236617,0.001789037,0.002753103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007160617,"about_ca_system_score_gemma":0.003304017,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002062205,"about_ca_topic_score_gemma":0.005168871,"domain_scores_codex":[0.9859708,0.009600833,0.001460428,0.001019029,0.001727312,0.0002216133],"domain_scores_gemma":[0.9299265,0.05792223,0.004813472,0.00334547,0.002595679,0.001396712],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.006992095,0.0007080897,0.04677905,0.005359011,0.003309421,0.0002878446,0.001130165,0.01357052,0.001040048,0.009306816,0.0926474,0.8188696],"study_design_scores_gemma":[0.01962084,0.007121126,0.1402382,0.01676447,0.00926671,0.00241902,0.002273954,0.2299538,0.01041782,0.1684471,0.3915124,0.001964643],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2772413,0.02535744,0.467168,0.04613808,0.002097588,0.01450115,0.08585575,0.02899436,0.05264619],"genre_scores_gemma":[0.3790613,0.004502469,0.5850728,0.004320202,0.0007840488,0.008568457,0.0116501,0.0009525716,0.005087956],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01584962,"threshold_uncertainty_score":0.08382183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1118753263542712,"score_gpt":0.3868165333139565,"score_spread":0.2749412069596853,"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."}}