{"id":"W2797064501","doi":"10.1016/j.biopsych.2018.02.1007","title":"S116. The Use of Arterial Spin Labeling Perfusion MRI for Automated Classification of Major Depression Disorder","year":2018,"lang":"en","type":"article","venue":"Biological Psychiatry","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary","funders":"","keywords":"Arterial spin labeling; Major depressive disorder; Cerebral blood flow; Neuroimaging; Magnetic resonance imaging; Depression (economics); Perfusion; Medicine; Multivariate statistics; Cardiology; Psychology; Radiology; Internal medicine; Psychiatry; Computer science; Machine learning","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":[],"consensus_categories":[],"category_scores_codex":[0.0001952736,0.000110573,0.0001647571,0.00003888098,0.0002623664,0.00001306533,0.0001791748,0.0001125211,0.00003595261],"category_scores_gemma":[0.003759411,0.00006075284,0.00008757762,0.0001855271,0.0003870629,0.00007040334,0.00009332933,0.00006716511,0.000008788787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009847133,"about_ca_system_score_gemma":0.00002566548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001311046,"about_ca_topic_score_gemma":0.0000239426,"domain_scores_codex":[0.9989161,0.0001589391,0.0002822555,0.0003549548,0.0001369823,0.0001507325],"domain_scores_gemma":[0.997602,0.001819708,0.0002116057,0.00024142,0.0001035167,0.00002171265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0006270561,0.0002391107,0.03023232,0.00001962523,0.000006721219,4.0891e-8,0.00005067488,0.00002590938,0.9566132,0.003338908,0.007412478,0.001433989],"study_design_scores_gemma":[0.002493191,0.002687066,0.8155679,0.0001589896,0.00005024493,0.000006563024,0.0002490665,0.05021604,0.09216549,0.004725736,0.03126221,0.0004174891],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.991459,0.0000643723,0.002407681,0.003937757,0.001426286,0.0004682238,0.00005915606,0.0001127214,0.00006485346],"genre_scores_gemma":[0.9957739,0.00001780309,0.003155587,0.0006809334,0.0002962779,0.00003973494,0.000006365929,0.000007617086,0.00002182445],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8644477,"threshold_uncertainty_score":0.4500638,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1149178600684665,"score_gpt":0.3286201794101055,"score_spread":0.2137023193416389,"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."}}