Cumulative effects of concussion in amateur athletes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PRIMARY OBJECTIVE: To examine the possibility that athletes with multiple concussions show cumulative effects of injury. METHODS AND PROCEDURES: Amateur athletes with a history of three or more concussions were carefully matched (gender, age, education and sport) with athletes with no prior concussions. All completed a computerized neuropsychological test battery at preseason (ImPACT) and then within 5 days of sustaining a concussion (mean = 1.7 days). MAIN OUTCOMES AND RESULTS: There were differences between groups in symptom reporting and memory performance. At baseline (i.e. preseason), athletes with multiple concussions reported more symptoms than athletes with no history of concussion. At approximately 2 days post-injury, athletes with multiple concussions scored significantly lower on memory testing than athletes with a single concussion. Athletes with multiple concussions were 7.7 times more likely to demonstrate a major drop in memory perfomance than athletes with no previous concussions. CONCLUSIONS: This study provides preliminary evidence to suggest that athletes with multiple concussions might have cumulative effects.
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.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 it