Analysis of Pediatric Facial Dog Bites
Bibliographic record
Abstract
The aim of this study was to characterize and report the epidemiological data regarding pediatric facial dog bites. For this study, a retrospective chart review was used. This study was performed at a large tertiary pediatric hospital. All children younger than 18 years who sought medical attention after a facial dog bite between January 1, 2003, and December 31, 2008, were included. Demographic and epidemiologic data were collected and analyzed. A total of 537 children were identified. The average age was 4.59 ± 3.36 years, with a slight male preponderance (52.0%). The majority of dog bites occurred in children 5 years of age or younger (68.0%). Almost all (89.8%) of the dogs were known to the children. When circumstances surrounding the bite were documented, over half (53.2%) of the cases were provoked. The most common breeds were mixed breed (23.0%), Labrador retriever (13.7%), Rottweiler (4.9%), and German shepherd (4.4%). Inpatient treatment was required in 121 (22.5%) patients with an average length of stay of 2.96 ± 2.77 days. Children 5 years or younger were more likely to be hospitalized than older children. Children 5 years old and younger are at high risk for being bitten in the face by a familiar dog and are more likely to require hospitalization than older children. Certain dog breeds are more likely to bite, and there is often a history of provocation. There is a tremendous financial and psychosocial burden associated with dog bites, and prevention strategies should focus on education with the aid of public policies and better documentation and reporting systems.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".