{"id":"W2900930986","doi":"10.1016/j.nicl.2018.11.006","title":"White matter injury predicts disrupted functional connectivity and microstructure in very preterm born neonates","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Advanced Neuroimaging Techniques and Applications","field":"Medicine","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Sinai Hospital; Canada Research Chairs; SickKids Foundation; University of Toronto; Children's Hospital of Western Ontario; Hospital for Sick Children; Western University","funders":"Canadian Institutes of Health Research; Ontario Brain Institute","keywords":"White matter; Corpus callosum; Fractional anisotropy; Corona radiata (embryology); Diffusion MRI; Interquartile range; Fasciculus; Medicine; Magnetic resonance imaging; Connectome; Diffuse axonal injury; Anatomy; Neuroscience; Functional connectivity; Internal medicine; Psychology; Traumatic brain injury; Radiology","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":[0.0006026045,0.0003720412,0.0002710778,0.0006743631,0.0001972215,0.000453025,0.0004074519,0.0005799273,0.0009987835],"category_scores_gemma":[0.005334356,0.0002021699,0.0003564814,0.0003565528,0.0004196125,0.0003275534,0.0005550629,0.0003987608,0.0001465154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003381696,"about_ca_system_score_gemma":0.0003040585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0031613,"about_ca_topic_score_gemma":0.002781268,"domain_scores_codex":[0.9997584,0.00005153401,0.00003602189,0.00007185677,0.00004945623,0.00003275923],"domain_scores_gemma":[0.9981019,0.0003915851,0.001093916,0.0000942612,0.0001478338,0.0001705942],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001372747,0.00001577326,0.9946427,0.00001792794,0.00004927008,0.0006445458,0.0001304872,0.0002236973,0.002030479,0.00003993686,0.00004102341,0.002026815],"study_design_scores_gemma":[0.000002071808,0.00007337646,0.9977801,0.0000149051,0.00001585083,0.001040089,0.0001380989,0.0004136708,0.0004200024,0.00006431299,0.00003415122,0.000003308215],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995938,0.0001005416,0.0001372314,0.00001897191,0.000001666945,0.000002505289,0.00005976262,0.000002963393,0.00008252804],"genre_scores_gemma":[0.999517,0.00009060072,0.0002094672,0.000008648376,0.000002846845,0.000007879259,0.000109612,0.000002320657,0.00005156718],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0031613,"threshold_uncertainty_score":0.006285846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06051169516384242,"score_gpt":0.3845515843053998,"score_spread":0.3240398891415574,"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."}}