{"id":"W4282933907","doi":"10.3389/fninf.2022.883223","title":"A Robust Modular Automated Neuroimaging Pipeline for Model Inputs to TheVirtualBrain","year":2022,"lang":"en","type":"article","venue":"Frontiers in Neuroinformatics","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Baycrest Hospital; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Medical Research Council; Compute Canada; BrightFocus Foundation","keywords":"Computer science; Biobank; Pipeline (software); Neuroimaging; Modalities; Connectome; Modular design; Leverage (statistics); Data science; Artificial intelligence; Scalability; Machine learning; Data mining; Database; Bioinformatics; Medicine","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":[0.001378503,0.001962731,0.0009749496,0.001716628,0.0009069805,0.002604387,0.002678124,0.001209326,0.03377054],"category_scores_gemma":[0.009105064,0.001301947,0.002497914,0.001046631,0.0004918576,0.002091571,0.002985932,0.002168774,0.01774864],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001382774,"about_ca_system_score_gemma":0.002520827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01366261,"about_ca_topic_score_gemma":0.02826309,"domain_scores_codex":[0.9993976,0.00009988857,0.00004843525,0.0002265723,0.0001768783,0.00005054085],"domain_scores_gemma":[0.9986224,0.0005470089,0.00007792609,0.0003385901,0.0003316304,0.00008234678],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000616238,0.0002204325,0.007746337,0.001016738,0.0006589163,0.001148944,0.0009888948,0.1263627,0.02188384,0.03110795,0.4602738,0.3479751],"study_design_scores_gemma":[0.0001338726,0.00006697766,0.003547089,0.0001360911,0.00009695689,0.0004062554,0.0001944895,0.769118,0.0157156,0.07260405,0.1378436,0.000137058],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004055526,0.0001584623,0.8381811,0.0005584323,0.0001529338,0.0002687041,0.01150475,0.1412396,0.003880336],"genre_scores_gemma":[0.09472102,0.0005353187,0.7810224,0.001095937,0.0001399104,0.002113916,0.06952298,0.03925768,0.01159085],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03377054,"threshold_uncertainty_score":0.1129737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04869408097994354,"score_gpt":0.2589611488286493,"score_spread":0.2102670678487058,"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."}}