{"id":"W3214691841","doi":"10.1002/hbm.25705","title":"Structural connectome differences in pediatric mild traumatic brain and orthopedic injury","year":2021,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Traumatic Brain Injury Research","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; University of British Columbia; Stollery Children's Hospital; Centre Hospitalier Universitaire Sainte-Justine; University of Alberta; Université de Montréal; Children's Hospital of Eastern Ontario; University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Alberta Children's Hospital Research Institute; Hotchkiss Brain Institute, University of Calgary","keywords":"Traumatic brain injury; Connectome; Fractional anisotropy; Diffusion MRI; Connectomics; Clustering coefficient; Psychology; Medicine; Physical medicine and rehabilitation; Neuroscience; Psychiatry; Cluster analysis; Magnetic resonance imaging; Artificial intelligence; Functional connectivity; Radiology; Computer science","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":[0.0003361979,0.0002652961,0.0002193337,0.0009986826,0.0002205206,0.0004159858,0.0001995919,0.0002265922,0.001479114],"category_scores_gemma":[0.001932426,0.0001363055,0.0002930824,0.0006728509,0.0003103228,0.0005803035,0.0004188793,0.0003143834,0.0001222357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005001203,"about_ca_system_score_gemma":0.0003498779,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008997381,"about_ca_topic_score_gemma":0.01613872,"domain_scores_codex":[0.9997919,0.00002497373,0.00001525663,0.00007125462,0.00004380393,0.00005278293],"domain_scores_gemma":[0.999341,0.0001052218,0.0003544718,0.0000392187,0.00006655547,0.00009361081],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001567584,0.00003383936,0.9849305,0.0000446763,0.000092394,0.0003397259,0.0006147839,0.0004560844,0.003192687,0.0003480006,0.0002240846,0.00956639],"study_design_scores_gemma":[0.000001908643,0.00005527608,0.9985077,0.000005829863,0.00001444621,0.0003681912,0.000299405,0.0002023346,0.0002611263,0.000124934,0.0001566434,0.000002310619],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9992242,0.0001069378,0.0001855088,0.0000273082,0.000002065313,0.000004269444,0.0002140991,0.000003490929,0.0002321967],"genre_scores_gemma":[0.9989135,0.0001545413,0.000374332,0.00001536492,0.000003329628,0.00001170992,0.0003889665,0.000003296787,0.0001349556],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008997381,"threshold_uncertainty_score":0.01789004,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1450090246994601,"score_gpt":0.3605027911680453,"score_spread":0.2154937664685852,"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."}}