{"id":"W4401916453","doi":"10.1016/j.bionps.2024.100107","title":"Biomarker discovery using machine learning in the psychosis spectrum","year":2024,"lang":"en","type":"article","venue":"Biomarkers in Neuropsychiatry","topic":"Schizophrenia research and treatment","field":"Medicine","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Institute of Mental Health","keywords":"Psychosis; Schizoaffective disorder; Biomarker discovery; Schizophrenia (object-oriented programming); Biomarker; Neuroimaging; Precision medicine; Psychology; Medicine; Artificial intelligence; Psychiatry; Machine learning; Data science; Neuroscience; Computer science; Pathology; Biology; Proteomics","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":[0.004626755,0.0006731232,0.001091842,0.00296653,0.0003403267,0.002258833,0.000447117,0.00095194,0.0005465067],"category_scores_gemma":[0.01007166,0.0003472943,0.0007097826,0.001708933,0.001189162,0.001353653,0.001560007,0.002031077,0.0002461169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008655257,"about_ca_system_score_gemma":0.001156252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001095577,"about_ca_topic_score_gemma":0.001335609,"domain_scores_codex":[0.9983283,0.001076376,0.0001094057,0.0002036096,0.0002102015,0.00007225663],"domain_scores_gemma":[0.9962623,0.002736405,0.0004296956,0.0001511825,0.0002796592,0.0001407683],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008130615,0.0003385886,0.08747484,0.001806721,0.0008835772,0.001385849,0.000407479,0.04678066,0.01185458,0.04899871,0.007620218,0.7916356],"study_design_scores_gemma":[0.0002670927,0.001145352,0.03209358,0.002776723,0.0007208352,0.003355064,0.0006889993,0.3691062,0.02403557,0.5096053,0.0558794,0.0003257568],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1485546,0.2546296,0.5470024,0.03663512,0.0009536592,0.0003006276,0.001140245,0.001350859,0.009432772],"genre_scores_gemma":[0.7243139,0.07968299,0.1892632,0.003822674,0.001068136,0.0001971849,0.0004846925,0.00006262026,0.001104574],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004626755,"threshold_uncertainty_score":0.0244689,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02937077258888117,"score_gpt":0.3176255656199821,"score_spread":0.2882547930311009,"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."}}