{"id":"W4380990775","doi":"10.1016/j.neuroimage.2023.120231","title":"Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge","year":2023,"lang":"en","type":"article","venue":"NeuroImage","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Sherbrooke","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute of Neurological Disorders and Stroke; National Institute on Aging; National Health and Medical Research Council; National Institute of Mental Health; Horizon 2020 Framework Programme; Narodowa Agencja Wymiany Akademickiej; Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México; Natural Sciences and Engineering Research Council of Canada; Centre Hospitalier Universitaire Vaudois; Centre d'Imagerie BioMédicale; Eunice Kennedy Shriver National Institute of Child Health and Human Development; Université de Lausanne; Hôpitaux Universitaires de Genève; Nvidia; Université de Genève; Academic Computer Centre Cyfronet, AGH University of Science and Technology; Polska Akademia Nauk; National Natural Science Foundation of China; National Institutes of Health; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institute on Drug Abuse; École Polytechnique Fédérale de Lausanne; Fundacja na rzecz Nauki Polskiej; European Commission; Consejo Nacional de Ciencia y Tecnología; National Institute of Allergy and Infectious Diseases; Agence Nationale de la Recherche; Ministerstwo Edukacji i Nauki; Infrastruktura PL-Grid; National Science Foundation","keywords":"Diffusion MRI; Computer science; Ground truth; Tractography; Diffusion; Monte Carlo method; Binary number; Task (project management); Scale (ratio); Functional connectivity; Artificial intelligence; Data mining; Algorithm; Pattern recognition (psychology); Magnetic resonance imaging; Mathematics; Statistics; Physics; Neuroscience; Psychology","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":[0.01115329,0.002208713,0.001892051,0.001412963,0.00139924,0.002288629,0.002114542,0.003352502,0.006043829],"category_scores_gemma":[0.07818089,0.0004945125,0.001811836,0.001111823,0.001974158,0.003529276,0.002864514,0.002881548,0.003665688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00135406,"about_ca_system_score_gemma":0.001868927,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01121361,"about_ca_topic_score_gemma":0.01321579,"domain_scores_codex":[0.9932438,0.003315664,0.0004370511,0.001506478,0.001029658,0.0004673858],"domain_scores_gemma":[0.9383838,0.04528628,0.001756412,0.008740194,0.003948173,0.001885163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01145668,0.002448678,0.06496724,0.004117284,0.002711928,0.002885452,0.001705102,0.2122941,0.008265278,0.02017879,0.3243499,0.3446195],"study_design_scores_gemma":[0.001636739,0.00315984,0.03976393,0.0006563111,0.0008087821,0.003376202,0.001909511,0.8148633,0.01139647,0.05566747,0.06648448,0.0002768861],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.76257,0.01713808,0.1229825,0.01139942,0.003185027,0.001057872,0.02777142,0.01488957,0.03900608],"genre_scores_gemma":[0.8657861,0.001148549,0.06436528,0.001613532,0.0004865293,0.0004197512,0.05335664,0.00298212,0.009841396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01121361,"threshold_uncertainty_score":0.05898499,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09610758939185464,"score_gpt":0.3536940188843558,"score_spread":0.2575864294925011,"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."}}