{"id":"W4311499956","doi":"10.1016/j.neuroimage.2022.119807","title":"BrainStat: A toolbox for brain-wide statistics and multimodal feature associations","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":126,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"National Institute of Biomedical Imaging and Bioengineering; Fonds de Recherche du Québec - Santé; Canadian Institutes of Health Research; Canada Research Chairs; Canada First Research Excellence Fund; National Institutes of Health; Institute for Basic Science; Centre Azrieli de recherche sur l'autisme, Institut et Hôpital Neurologiques de Montréal; National Institute of Mental Health; Hospital for Sick Children; Max-Planck-Gesellschaft; National Alliance for Research on Schizophrenia and Depression; Health Canada; McGill University; Brain and Behavior Research Foundation; Natural Sciences and Engineering Research Council of Canada; Fondation Brain Canada","keywords":"Toolbox; Computer science; Univariate; Python (programming language); Neuroimaging; Artificial intelligence; Multivariate statistics; Feature (linguistics); Neuroinformatics; Machine learning; Pattern recognition (psychology); Psychology; Data science; Programming language; Neuroscience","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003676315,0.002691829,0.00169971,0.002807726,0.0005616275,0.003070181,0.003170319,0.00143999,0.07077622],"category_scores_gemma":[0.01742162,0.001657186,0.002405384,0.002245972,0.0008281561,0.002540956,0.003713318,0.004060606,0.04014566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006486819,"about_ca_system_score_gemma":0.002671931,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002282969,"about_ca_topic_score_gemma":0.00454312,"domain_scores_codex":[0.9989356,0.0002795296,0.0001546665,0.0002534846,0.0002975901,0.00007909106],"domain_scores_gemma":[0.9940752,0.003905437,0.0004031837,0.000795139,0.0005981499,0.0002228639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0005365586,0.0001305681,0.002286965,0.002849349,0.0008219918,0.0009978128,0.0006766022,0.02182595,0.01438814,0.04243032,0.6382243,0.2748314],"study_design_scores_gemma":[0.0006470631,0.0001309511,0.005364851,0.0007103339,0.0002578647,0.00163017,0.0001950122,0.2151771,0.02122159,0.2496193,0.5046868,0.0003590345],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.001154302,0.0005186786,0.7560858,0.0003427733,0.0001780653,0.0001379516,0.02551354,0.2136627,0.002406301],"genre_scores_gemma":[0.02243322,0.001141795,0.831283,0.0009694959,0.000215977,0.002983277,0.04372964,0.09187669,0.00536693],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.07077622,"threshold_uncertainty_score":0.23677,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03164047274613558,"score_gpt":0.2844539397633309,"score_spread":0.2528134670171954,"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."}}