Analysis of Dog Bites in Children Who Are Younger Than 17 Years
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
OBJECTIVES: This study focuses on the pattern of incidence, mechanisms, and circumstances of accident and injury in a series of pediatric patients who sustained dog bites. METHODS: In our retrospective survey, the medical charts of all children who were younger than 17 years and sought medical attention after a dog bite between 1994 and 2003 were reviewed. To obtain the total number of each dog breed in the administrative district, we analyzed 5873 files from the community dog registers. For establishment of a risk index, the representation of a dog breed among the total canine population was divided by the frequency of dog bites from this breed. RESULTS: A total of 341 children (mean age: 5.9 years) were identified. The annual incidence of dog bites was 0.5 per 1000 children between 0 and 16 years of age. Incidence was highest in 1-year-old patients and decreased with increasing age. The relative risk for a dog attack by a German shepherd or a Doberman was approximately 5 times higher than that of a Labrador/retriever or cross-breed. The vast majority (82%) of the dogs were familiar to the children. Most (322; 94%) of the children had injuries to 1 body region; in the remaining 19 (6%) children, up to 3 body regions were injured. Of 357 injuries, the face, head, and neck region was the leading site affected (50%). Inpatient treatment was required in 93 (27%) patients. CONCLUSIONS: Dog bites in children are frequent and influenced by the breed-related behavior of dogs, dog owners, children, and parents. Therefore, prevention strategies should focus on public education and training of dogs and their owners. Children who are younger than 10 years represent the high-risk group for dog attacks.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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