{"id":"W2902621341","doi":"10.1089/brain.2018.0582","title":"Asymmetric Insular Connectomics Revealed by Diffusion Magnetic Resonance Imaging Analysis of Healthy Brain Development","year":2018,"lang":"en","type":"article","venue":"Brain Connectivity","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Francis Xavier University","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development; National Institute of Neurological Disorders and Stroke; National Institute of Mental Health; National Institutes of Health; St. Francis Xavier University","keywords":"Connectomics; Neuroscience; Insula; Psychology; Connectome; Tractography; Diffusion MRI; Population; Functional magnetic resonance imaging; Lateralization of brain function; Magnetic resonance imaging; Medicine; Functional connectivity","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":["metaresearch","metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002147392,0.0004864308,0.001005548,0.001297665,0.0008284246,0.00007088118,0.0005588385,0.0001406918,0.0001398493],"category_scores_gemma":[0.05308471,0.0005062268,0.000267549,0.006344634,0.0007101822,0.0003402403,0.0004948708,0.0003466561,0.00005207642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000425489,"about_ca_system_score_gemma":0.0002849272,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002710547,"about_ca_topic_score_gemma":0.000594561,"domain_scores_codex":[0.9948003,0.001037679,0.0008171503,0.001619249,0.0009152031,0.0008103995],"domain_scores_gemma":[0.9729149,0.02515092,0.0004906512,0.0008701149,0.0003549216,0.0002185154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00143119,0.001918438,0.2286627,0.0001641443,0.0003240135,0.00003655964,0.002396415,0.00004158995,0.4258903,0.005073633,0.1062324,0.2278287],"study_design_scores_gemma":[0.003563433,0.001049022,0.6323971,0.00009535023,0.0002568154,0.0000314663,0.0002017044,0.01862013,0.1158564,0.00104996,0.2255507,0.001327843],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9743249,0.001865694,0.005627266,0.01477762,0.0006459393,0.0007271048,0.0001791999,0.0002342754,0.001618013],"genre_scores_gemma":[0.9827545,0.00005512378,0.0006328089,0.01575789,0.0001545359,0.00007630754,0.00001607763,0.00005379905,0.0004990067],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4037344,"threshold_uncertainty_score":0.9997389,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02107178433970622,"score_gpt":0.2706624849761882,"score_spread":0.249590700636482,"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."}}