A 14-year-old competitive, high-level athlete with unilateral low back pain: case report.
Bibliographic record
Abstract
OBJECTIVE: To detail the presentation of a male adolescent competitive high-level soccer player with left sided low back pain that occurred while playing soccer. This case will outline the importance of early detection, risk of progression and management of active spondylolysis in adolescent athletes. CLINICAL FEATURES: The patient initially presented to a chiropractic sport specialist with left sided low back pain (9/10 on numeric pain scale rating) while kicking soccer balls with his left leg of one month duration. He was initially diagnosed with mechanical low back pain and successfully treated for acute pain management including removal from sport specific training and competition, soft tissue therapy and advice to rest. The chief complaint returned however, when the athlete resumed training and competition. A plain film imaging report suggested only postural alterations in an otherwise normal study of the lumbar spine. Computed tomography images taken three months later revealed a fracture at the left L5 pars interarticularis. SUMMARY: The early detection of spondylolysis combined with an effective plan of management including rest and conservative therapy with a progressive return to play may allow competitive athletes to resume participation at an elite level.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".