{"id":"W1999857562","doi":"10.1089/neu.2005.22.76","title":"Changes in White Matter in Long-Term Survivors of Severe Non-Missile Traumatic Brain Injury: A Computational Analysis of Magnetic Resonance Images","year":2005,"lang":"en","type":"article","venue":"Journal of Neurotrauma","topic":"Traumatic Brain Injury and Neurovascular Disturbances","field":"Medicine","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"Montreal Neurological Institute and Hospital; McGill University","funders":"","keywords":"Corpus callosum; White matter; Fornix; Traumatic brain injury; Magnetic resonance imaging; Internal capsule; Voxel; Psychology; Coma (optics); Medicine; Neuroscience; Ophthalmology; Hippocampus; Radiology; Psychiatry; Physics","routes":{"ca_aff":true,"ca_fund":false,"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":[],"consensus_categories":[],"category_scores_codex":[0.0006408637,0.0002123861,0.001066269,0.001268707,0.00001898287,0.00001427897,0.0002365022,0.00008186913,0.0004931375],"category_scores_gemma":[0.0001182639,0.0001840987,0.0003471048,0.001337154,0.0001392698,0.0001867237,0.00002610896,0.0003723071,0.000003306325],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000438364,"about_ca_system_score_gemma":0.00007487676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002520298,"about_ca_topic_score_gemma":0.0006010327,"domain_scores_codex":[0.9974288,0.0002251683,0.001260604,0.0002334525,0.0006085882,0.0002433689],"domain_scores_gemma":[0.9984422,0.0003593365,0.0006696366,0.0002717028,0.0001540863,0.0001030253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007161089,0.0008810544,0.9673705,0.0006114679,0.0002050806,0.0001620558,0.002007251,0.003257384,0.002025568,0.000004241223,0.0005564196,0.02220284],"study_design_scores_gemma":[0.002041491,0.0008147913,0.99347,0.0006928197,0.0003616627,0.0001828812,0.0001134629,0.001071168,0.001040697,0.00002600877,0.00005114785,0.0001339344],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951801,0.0009135872,0.00005315641,0.003197303,0.00006648868,0.0002859455,0.00003620601,0.000004677891,0.0002624962],"genre_scores_gemma":[0.9980182,0.0001161136,0.001002769,0.0006244432,0.00005663573,0.000006837913,0.000006785782,0.00002200484,0.0001461931],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0260994,"threshold_uncertainty_score":0.7507325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0285393689837307,"score_gpt":0.3058576419426666,"score_spread":0.2773182729589359,"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."}}