Bibliographic record
Abstract
CONTEXT: Low back pain in young athletes is a common complaint and should be taken seriously. It frequently results from a structural injury that requires a high degree of suspicion to diagnose and treat appropriately. EVIDENCE ACQUISITION: A Medline search was conducted from 1996 to May 2008 using the search terms "low back pain in children" and "low back pain in athletes." Known texts on injuries in young athletes were also reviewed. References in retrieved articles were additionally searched for relevant articles. Sources were included if they contained information regarding diagnosis and treatment of causes of low back pain in children. RESULTS: Low back pain is associated with sports involving repetitive extension, flexion, and rotation, such as gymnastics, dance, and soccer. Both acute and overuse injuries occur, although overuse injuries are more common. Young athletes who present with low back pain have a high incidence of structural injuries such as spondylolysis and other injuries to the posterior elements of the spine. Disc-related pathology is much less common. Simple muscle strains are much less likely in this population and should be a diagnosis of exclusion only. CONCLUSION: Young athletes who present with low back pain are more likely to have structural injuries and therefore should be investigated fully. Muscle strain should be a diagnosis of exclusion. Treatment should address flexibility and muscle imbalances. Injuries can be prevented by recognizing and addressing risk factors. Return to sport should be a gradual process once the pain has resolved and the athlete has regained full strength.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".