Quantitative neuroimaging assessment of cerebrovascular responsiveness in individual sports-related concussion patients
Bibliographic record
Abstract
Concussion is a complex pathophysiological process affecting the brain, induced by traumatic biomechanical forces. From 2005 to 2010, approximately 7,000 Manitobans aged 14-18 years were diagnosed with a concussion. About half of all pediatric concussions occur during sport and our work shows that hockey is the most common sport resulting in a concussion among youth. OBJECTIVE - The overall objective of this study is to follow longitudinally two Winnipeg youth hockey teams to perform a comprehensive assessment of neurological, physiological, neuro-imaging, neuropsychological, and psychosocial functioning and measure these parameters before and after one hockey season and follow the two teams for a second season. We will examine these parameters among players who do and not sustain a concussion while playing hockey. INTERDISCIPLINARY TEAM - To accomplish our objectives, we will work within our recently established multi-disciplinary team of concussion researchers (CNCN). Our team includes a neurosurgeon who will treat all of the athletes (Dr Michael Ellis), a neuroanesthetist (Dr Alan Mutch) to conduct the MRI CO2 brain stress test, an exercise physiologist (Dean Cordingley) to conduct graded treadmill testing with an athletic therapist (Richard Girardin), a neuropsychologist (Dr Lesley Ritchie) to perform neuropsychological testing, and a sport injury epidemiologist (Dr Kelly Russell) who will provide methodological and statistical expertise. Additionally, we employ two research assistants.
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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 | 0.000 |
| 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) | 0.001 | 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".