A comparison in a youth population between those with and without a history of concussion using biomechanical reconstruction
Bibliographic record
Abstract
OBJECTIVE Concussion is a common topic of research as a result of the short- and long-term effects it can have on the affected individual. Of particular interest is whether previous concussions can lead to a biomechanical susceptibility, or vulnerability, to incurring further head injuries, particularly for youth populations. The purpose of this research was to compare the impact biomechanics of a concussive event in terms of acceleration and brain strains of 2 groups of youths: those who had incurred a previous concussion and those who had not. It was hypothesized that the youths with a history of concussion would have lower-magnitude biomechanical impact measures than those who had never suffered a previous concussion. METHODS Youths who had suffered a concussion were recruited from emergency departments across Canada. This pool of patients was then separated into 2 categories based on their history of concussion: those who had incurred 1 or more previous concussions, and those who had never suffered a concussion. The impact event that resulted in the brain injury was reconstructed biomechanically using computational, physical, and finite element modeling techniques. The output of the events was measured in biomechanical parameters such as energy, force, acceleration, and brain tissue strain to determine if those patients who had a previous concussion sustained a brain injury at lower magnitudes than those who had no previously reported concussion. RESULTS The results demonstrated that there was no biomechanical variable that could distinguish between the concussion groups with a history of concussion versus no history of concussion. CONCLUSIONS The results suggest that there is no measureable biomechanical vulnerability to head impact related to a history of concussions in this youth population. This may be a reflection of the long time between the previous concussion and the one reconstructed in the laboratory, where such a long period has been associated with recovery from injury.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".