{"id":"W2182367256","doi":"10.1016/j.neuroimage.2015.09.041","title":"Generative models of the human connectome","year":2015,"lang":"en","type":"article","venue":"NeuroImage","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":343,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Division of Graduate Education; National Institute of Mental Health; NIH Blueprint for Neuroscience Research; National Institute on Aging; National Key Research and Development Program of China; Natural Sciences and Engineering Research Council of Canada; Medical Research Council; McDonnell Center for Systems Neuroscience; Fondation Leenaards; National Institute for Health and Care Research; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Wellcome Trust; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; National Institutes of Health; National Science Foundation; James S. McDonnell Foundation","keywords":"Connectome; Generative grammar; Human Connectome Project; Generative model; Computer science; Topology (electrical circuits); Function (biology); Artificial intelligence; Machine learning; Neuroscience; Functional connectivity; Mathematics; Psychology; Biology; Evolutionary biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001135473,0.0005803535,0.000555247,0.001436606,0.0005010045,0.001052759,0.001023008,0.001562622,0.004895423],"category_scores_gemma":[0.006616007,0.0005781312,0.001508025,0.0009312291,0.001144429,0.001359188,0.0007791831,0.001075661,0.0006298064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00143354,"about_ca_system_score_gemma":0.0004541293,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007882768,"about_ca_topic_score_gemma":0.01081096,"domain_scores_codex":[0.9996033,0.0001928302,0.00001308648,0.0001105447,0.00004089699,0.00003932897],"domain_scores_gemma":[0.9976223,0.001649451,0.0002288673,0.0002229077,0.0001539188,0.0001225749],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007352237,0.00002964092,0.004926474,0.00006617434,0.00007825826,0.0002607,0.0002846111,0.8842145,0.001423043,0.09792225,0.003671718,0.007049211],"study_design_scores_gemma":[0.00002007518,0.00001275225,0.001579706,0.00002193061,0.00001767504,0.0001610561,0.00003900574,0.9322647,0.0001828632,0.06413053,0.00155493,0.00001479785],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5622159,0.001430748,0.4103726,0.002670452,0.0001071001,0.0001453758,0.005907232,0.0009638589,0.01618671],"genre_scores_gemma":[0.9629919,0.0006001778,0.02736286,0.0002738859,0.00005885774,0.0003271136,0.002920543,0.0002028514,0.005261915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007882768,"threshold_uncertainty_score":0.01637679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.159628908401934,"score_gpt":0.3077958205326094,"score_spread":0.1481669121306754,"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."}}