Serious Impact of Handlebar Injuries
Bibliographic record
Abstract
BACKGROUND: Injuries from bicycles is a leading cause of trauma in children. We sought to investigate the epidemiology of bicycle handlebar injuries. METHODS: A retrospective analysis of bicycle trauma treated at our institution was preformed. RESULTS: A total of 462 children younger than 17 years had bicycle trauma. Abdominal handlebar injuries, representing 9% of bicycle injuries, contributed to 19% of all internal organ injuries, and 45.4% of solid, 87.5% of hollow, 66.6% of vascular or lymphatic, and 100% of pancreatic injuries. Handlebar injuries were 10 times more likely to cause severe injury, yet more than half of the children were misdiagnosed at their initial presentation. Delayed diagnosis and longer hospital stays were observed in handlebar injuries to the abdomen. CONCLUSION: Physicians should be aware of the serious impact of bicycle handlebar injury to the abdomen. The mechanism alone should raise the suspicion of internal organ injury, and timely imaging and surgical consultation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".