{"id":"W2181270872","doi":"10.3389/fnhum.2015.00585","title":"Probabilistic atlases of default mode, executive control and salience network white matter tracts: an fMRI-guided diffusion tensor imaging and tractography study","year":2015,"lang":"en","type":"article","venue":"Frontiers in Human Neuroscience","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Manitoba","funders":"Canadian Institutes of Health Research; National Institutes of Health; University of Manitoba; National Institute of Mental Health; Health Sciences Centre Foundation","keywords":"Diffusion MRI; Default mode network; White matter; Tractography; Resting state fMRI; Neuroscience; Human Connectome Project; Salience (neuroscience); Artificial intelligence; Task-positive network; Psychology; Neuroimaging; Computer science; Pattern recognition (psychology); Functional magnetic resonance imaging; Medicine; Functional connectivity; Magnetic resonance imaging; Radiology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002378199,0.0001772684,0.0003290394,0.0001852732,0.0001469349,0.00004217898,0.0001751272,0.00002624741,6.326276e-7],"category_scores_gemma":[0.0001194157,0.000154229,0.00002617983,0.0004172998,0.0006969615,0.0003143938,0.00007030024,0.0001959605,4.739724e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002338882,"about_ca_system_score_gemma":0.00002430432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003702131,"about_ca_topic_score_gemma":0.000005719622,"domain_scores_codex":[0.9984148,0.00008618262,0.0003409661,0.0006125905,0.0002607409,0.0002847591],"domain_scores_gemma":[0.9991544,0.00003887881,0.0001580418,0.0003608512,0.00009219648,0.0001956223],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005972567,0.0003844686,0.9933541,0.00001857827,0.000001091098,0.00002323439,0.0005638452,0.0007757444,0.003350472,0.00005431915,0.001169902,0.0002445269],"study_design_scores_gemma":[0.001367469,0.0005105708,0.953185,0.00007049352,0.00004521557,0.00006782669,0.0006001069,0.04071625,0.00006351362,0.003075236,0.0001310341,0.0001673357],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9579098,0.00009656398,0.04016605,0.0003075032,0.00008842277,0.001212339,0.00001051624,0.00007054718,0.0001382586],"genre_scores_gemma":[0.9917235,0.00001870468,0.007573796,0.0005063004,0.00002297878,0.00008301435,0.000002006016,0.00001894725,0.00005072842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04016915,"threshold_uncertainty_score":0.6289276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0468302688176115,"score_gpt":0.3404702059645135,"score_spread":0.293639937146902,"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."}}