{"id":"W2792267984","doi":"10.1016/j.nicl.2018.03.026","title":"Automated versus manual segmentation of brain region volumes in former football players","year":2018,"lang":"en","type":"article","venue":"NeuroImage Clinical","topic":"Traumatic Brain Injury Research","field":"Medicine","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Biomedical Imaging and Bioengineering; National Institute on Aging; Canadian Institutes of Health Research; National Institutes of Health; National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences; Deutscher Akademischer Austauschdienst; Australian Football League; National Football League Players Association; Ludwig-Maximilians-Universität München; JetBlue","keywords":"Segmentation; Intraclass correlation; Corpus callosum; Neuroimaging; Brain size; Psychology; Medicine; Magnetic resonance imaging; Artificial intelligence; Neuroscience; Computer science; Radiology; Developmental psychology","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":[0.001418937,0.0003340072,0.0003011206,0.001575908,0.0002923607,0.000908054,0.0004187843,0.0005119033,0.001050303],"category_scores_gemma":[0.00542496,0.000278864,0.0002267303,0.0003737671,0.0007044728,0.0005492271,0.0004281311,0.000136749,0.0003379957],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004983487,"about_ca_system_score_gemma":0.0003098075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008382292,"about_ca_topic_score_gemma":0.01838884,"domain_scores_codex":[0.9990507,0.0002214679,0.00007800182,0.0003194127,0.0002374586,0.00009297311],"domain_scores_gemma":[0.9976477,0.0005378975,0.001068596,0.0002394227,0.0004036606,0.00010274],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002335455,0.0001651841,0.8798191,0.0001769362,0.0002998299,0.0005283795,0.001677582,0.003631081,0.04331744,0.0001691729,0.000480648,0.06739914],"study_design_scores_gemma":[0.0000187583,0.0002678911,0.9895511,0.0000210553,0.00003611298,0.0005890938,0.0002655593,0.004919874,0.004027266,0.00005953354,0.0002308811,0.00001286137],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9978502,0.0001073251,0.001586458,0.0000127003,0.000003224738,0.00001345775,0.00006691994,0.00003118923,0.0003286472],"genre_scores_gemma":[0.9977468,0.00004354748,0.001764482,0.0000141604,0.000006650657,0.00001343872,0.0001602752,0.00001438021,0.0002363377],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008382292,"threshold_uncertainty_score":0.01666701,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2053413063757689,"score_gpt":0.4859791206428173,"score_spread":0.2806378142670484,"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."}}