{"id":"W2611999549","doi":"10.1016/j.schres.2017.05.001","title":"A computational algorithm for personalized medicine in schizophrenia","year":2017,"lang":"en","type":"article","venue":"Schizophrenia Research","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University Health Network; University of Toronto","funders":"National Institute of Mental Health; Eli Lilly and Company","keywords":"Ziprasidone; Quetiapine; Olanzapine; Positive and Negative Syndrome Scale; Antipsychotic; Schizophrenia (object-oriented programming); Risperidone; Single-nucleotide polymorphism; Psychiatry; Medicine; Psychology; Internal medicine; Psychosis; Biology; Genetics; Gene","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":[0.001827497,0.000594359,0.0012243,0.00100736,0.0009475562,0.001298295,0.001739516,0.001780222,0.006017475],"category_scores_gemma":[0.008147798,0.000536027,0.001086723,0.001196984,0.0006375347,0.0009850111,0.001860733,0.001458331,0.0007015707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001128507,"about_ca_system_score_gemma":0.002928884,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01194625,"about_ca_topic_score_gemma":0.01237535,"domain_scores_codex":[0.9994339,0.0002702839,0.00004216962,0.00009804488,0.0001070864,0.00004838004],"domain_scores_gemma":[0.996908,0.002474013,0.00006884587,0.0001740767,0.0002954157,0.00007966498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001709847,0.00008632906,0.001342654,0.00007233454,0.00008867043,0.00008528263,0.00006056251,0.8569632,0.0002714977,0.01606264,0.004224914,0.120571],"study_design_scores_gemma":[0.0000302383,0.000009805606,0.00006242487,0.000006679392,0.00001186859,0.00001775112,0.000006010017,0.989595,0.00007691332,0.009786434,0.0003942539,0.000002691961],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01867006,0.0003315565,0.9751082,0.001330109,0.00009993569,0.0001306318,0.0004012157,0.001126393,0.002801792],"genre_scores_gemma":[0.2511287,0.000267062,0.7435104,0.0005192734,0.000117892,0.0005252477,0.0006629603,0.0001389051,0.003129525],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01194625,"threshold_uncertainty_score":0.02375346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06406363173060137,"score_gpt":0.4014787702575539,"score_spread":0.3374151385269525,"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."}}