{"id":"W2221287886","doi":"10.1503/jpn.140377","title":"Voxel-based morphometry analysis reveals frontal brain differences in participants with ADHD and their unaffected siblings","year":2016,"lang":"en","type":"article","venue":"Journal of Psychiatry and Neuroscience","topic":"Attention Deficit Hyperactivity Disorder","field":"Medicine","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Cilag; National Institute of Biomedical Imaging and Bioengineering; National Institutes of Health; Radboud Universitair Medisch Centrum; Servier; Accare; Nederlandse Organisatie voor Wetenschappelijk Onderzoek; Vrije Universiteit Amsterdam; National Institute of Mental Health; Radboud Universiteit; Eli Lilly and Company; Universitair Medisch Centrum Groningen; ZonMw","keywords":"Precentral gyrus; Grey matter; Voxel-based morphometry; Psychology; Orbitofrontal cortex; Superior frontal gyrus; Attention deficit hyperactivity disorder; Cognition; Voxel; Brain size; Neuroimaging; Audiology; Superior temporal gyrus; Clinical psychology; Neuroscience; Medicine; Prefrontal cortex; Magnetic resonance imaging; Functional magnetic resonance imaging","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.0005360089,0.0003203621,0.0003206004,0.0008238766,0.0003870409,0.0003850629,0.0002978948,0.0003139212,0.002367691],"category_scores_gemma":[0.001898155,0.0001802224,0.000297312,0.0003618666,0.0003390468,0.0002462791,0.0003382484,0.0001889577,0.0001866305],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003174519,"about_ca_system_score_gemma":0.0001901811,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005175876,"about_ca_topic_score_gemma":0.006879756,"domain_scores_codex":[0.9997547,0.0000417682,0.00003243345,0.00008465667,0.00005166959,0.00003470855],"domain_scores_gemma":[0.9995197,0.0001182955,0.0002013295,0.00005239083,0.00005548694,0.0000527329],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004346558,0.00006212031,0.9779659,0.0000301225,0.0001645938,0.00137613,0.00137261,0.00007307684,0.01320367,0.00007002208,0.0002087455,0.005038286],"study_design_scores_gemma":[0.000006540021,0.0000604089,0.9973205,0.000002794507,0.00002901,0.001555626,0.0003277949,0.00009432583,0.000469423,0.000045664,0.00008535626,0.00000266233],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997459,0.0000323651,0.00005419777,0.000007738263,8.74246e-7,0.000002811535,0.00008165439,0.00000319123,0.00007122321],"genre_scores_gemma":[0.9996538,0.00001657947,0.0001309435,0.000004544681,0.000001077761,0.000004543095,0.0001331218,0.000002279072,0.00005298069],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005175876,"threshold_uncertainty_score":0.01029152,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04603396297960385,"score_gpt":0.3140007945673004,"score_spread":0.2679668315876965,"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."}}