{"id":"W4375945060","doi":"10.1016/j.pscychresns.2023.111655","title":"Multi-study evaluation of neuroimaging-based prediction of medication class in mood disorders","year":2023,"lang":"en","type":"article","venue":"Psychiatry Research Neuroimaging","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"London Health Sciences Centre; Lawson Health Research Institute; Western University","funders":"National Institute of Mental Health; National Institutes of Health; National Science Foundation","keywords":"Generalizability theory; Neuroimaging; Major depressive disorder; Mood; Bipolar disorder; Support vector machine; Mood disorders; Psychology; Artificial intelligence; Clinical psychology; Machine learning; Psychiatry; Computer science; Anxiety; Developmental psychology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.006800498,0.0001765371,0.0002559296,0.001664908,0.0002566875,0.00002995574,0.0004352816,0.00003964046,0.00001948273],"category_scores_gemma":[0.0222351,0.0001884277,0.00008252901,0.003805586,0.0004171222,0.0003289753,0.0002110362,0.0006091826,0.00002222507],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001049347,"about_ca_system_score_gemma":0.0004409666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001928893,"about_ca_topic_score_gemma":0.0005894949,"domain_scores_codex":[0.9925265,0.002544525,0.0006000223,0.0009222402,0.002900512,0.0005061757],"domain_scores_gemma":[0.9947186,0.003949903,0.0002036161,0.0006321879,0.0004228965,0.00007287078],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001164071,0.001488562,0.8890592,0.0001166848,0.00001040196,0.00000179004,0.0006384386,0.01096608,0.09365325,0.0001112214,0.0009615138,0.002876453],"study_design_scores_gemma":[0.001853573,0.0002284795,0.6135501,0.00004696372,0.00001439499,9.898864e-7,0.0007738563,0.3811534,0.001442259,0.0008210585,0.00004234155,0.00007258497],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9766121,0.00004926809,0.0001620556,0.01934252,0.001096106,0.001617295,0.00003700305,0.0001456514,0.0009380303],"genre_scores_gemma":[0.9993634,0.00002971303,0.0001025512,0.0001314594,0.00006210907,0.0002467592,0.000008145897,0.00003883014,0.00001709717],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3701873,"threshold_uncertainty_score":0.986001,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2119011900643034,"score_gpt":0.42851847758156,"score_spread":0.2166172875172566,"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."}}