Changes in cortical thickness in pediatric sports-related concussion: a pilot study
Bibliographic record
Abstract
Sports-related concussion (SRC) is a form of traumatic brain injury (TBI) that is thought to represent a functional, rather than a structural brain injury. Recent studies however have implicated SRC as a potential risk factor for the long-term development of neurodegenerative disease such as chronic traumatic encephalopathy (CTE), a condition characterized by widespread atrophy of numerous cortical and subcortical brain structures. The objective of this study is to retrospectively examine the relationship between concussion history, concussion symptom burden, and volumetric grey and white matter volume in children and adolescents with symptomatic SRC compared to healthy non-concussed controls. Volumetric studies will be carried out using Freesurfer software in a blinded fashion in approximately 30 adolescent SRC patients evaluated at the Pan Am Concussion Program, Winnipeg, Manitoba and 30 normal control subjects. All subjects included in this pilot study have undergone volumetric T1-weighted magnetic resonance imaging (MRI) as a part of a previous neuroimaging research study at the Kleysen Institute of Advanced Medicine. The results of this study will provide insight into the effect of concussion history and symptom burden on grey and white matter volumes in children and adolescents. Region of interest volumetric grey and matter analysis may also yield a potential quantitative biomarker that could be used to estimate the cumulative effects of concussion and the risk of developing long-term effects such as neurodegenerative disease and CTE.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".