Concussions and their consequences: current diagnosis, management and prevention
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
oncussion is the most common type of mild traumatic brain injury and can have serious consequences. Not just confined to high-profile athletes, concussions are frequent in all age groups and in a variety of settings, such as the work environment, motor vehicle crashes, sports and recreation, and falls at home among older people. Concussion is defined by the International Consensus Conference on Concussion in Sports as "a complex pathophysiological process affecting the brain, induced by biomechanical forces." 1 Concussion is the preferred term be cause of its familiarity to the public. Since 2000, international expert panels have clari fied the definition and modified the management of concussion; these changes have affected recommendations for return to work, school and sport for those experiencing a concussion. he importance of accurate and timely recognition and management stems from the consequences of misdiagnosis or faulty management that can lead to major disability or death, in both the short and long term. Second-impact syndrome occurs when a concussed person, especially a younger person, returns to play before complete recovery and sustains a second brain injury. However, malignant brain swelling can occur even without a second injury. 3 Also, repeated concussions may cause delayed posttraumatic brain degeneration, leading to dementia and movement disorders similar to Alzheimer and Parkinson diseases. 4 Thus, it is important for practitioners to know the current principles of recognition and management of concussions, including the physical, cognitive and emotional effects and the guidelines for return to play, work or school.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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