{"id":"W4294968711","doi":"10.1016/j.neuroimage.2022.119612","title":"Micapipe: A pipeline for multimodal neuroimaging and connectome analysis","year":2022,"lang":"en","type":"article","venue":"NeuroImage","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":123,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; McGill University; Montreal Neurological Institute and Hospital","funders":"Centre Azrieli de recherche sur l'autisme, Institut et Hôpital Neurologiques de Montréal; National Institute of Mental Health; Ministry of Science, ICT and Future Planning; Fonds de Recherche du Québec - Santé; National Institute of Biomedical Imaging and Bioengineering; Canadian Institutes of Health Research; Canadian Open Neuroscience Platform; Health Canada; Natural Sciences and Engineering Research Council of Canada; Institute for Information and Communications Technology Promotion; Hospital for Sick Children; National Research Foundation of Korea; Inha University; Universidad Nacional Autónoma de México; Savoy Foundation; Universiteit Maastricht; National Research Foundation; Institute for Basic Science; Consejo Nacional de Ciencia y Tecnología; National Institutes of Health; Canada First Research Excellence Fund; Canada Research Chairs; McGill University; Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México; Ministry of Science and ICT, South Korea; Fondation Brain Canada","keywords":"Human Connectome Project; Connectome; Neuroimaging; Computer science; Tractography; Connectomics; Diffusion MRI; Artificial intelligence; Functional magnetic resonance imaging; Neuroscience; Pattern recognition (psychology); Functional connectivity; Psychology; Magnetic resonance imaging; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003086367,0.0002033076,0.0003157133,0.0003812808,0.0009323877,0.00008047059,0.0002521304,0.0000159833,0.0001353297],"category_scores_gemma":[0.006217585,0.0002221233,0.0001870899,0.001049242,0.0001591936,0.0001793731,0.0005039165,0.0002815097,0.000008057172],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004043404,"about_ca_system_score_gemma":0.00002515977,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002677992,"about_ca_topic_score_gemma":0.000009880338,"domain_scores_codex":[0.9977767,0.0002632522,0.0002315445,0.0009958991,0.0003642795,0.0003683469],"domain_scores_gemma":[0.9933397,0.00607525,0.0001062267,0.0003494686,0.00004625333,0.00008310442],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000410115,0.000332981,0.007699304,0.00004815944,0.00008658112,0.0001716697,0.0004840997,0.003233396,0.9661788,0.002016096,0.01471853,0.004620258],"study_design_scores_gemma":[0.00494565,0.0007886406,0.04944203,0.000004296068,0.0008338426,0.0003578562,0.000439724,0.6993003,0.04542645,0.002309744,0.1949338,0.001217637],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9714073,0.000130406,0.006199999,0.01843565,0.0007031334,0.0008655867,0.0005730604,0.0003554097,0.001329478],"genre_scores_gemma":[0.9864305,0.0000107548,0.0003506324,0.01206044,0.00008449847,0.0002137245,0.000009532841,0.00003688064,0.0008030466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9207523,"threshold_uncertainty_score":0.9057926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03613760562316639,"score_gpt":0.2831048872553093,"score_spread":0.2469672816321429,"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."}}