Rate of pediatric tap water scald injuries in eastern Ontario
Bibliographic record
Abstract
BACKGROUND: Tap water scalds can be devastating and are entirely preventable. This topic has received notable attention in Canada in recent years, with a national campaign in 2001 directed at parents recommending that they lower the water temperature of their home water heater. This campaign has been evaluated and reported as a successful population-based intervention. OBJECTIVES: The present study evaluated the rate of pediatric tap water scalds in Ottawa, Ontario over the 10-year period from 1993 to 2002 in an attempt to identify the impact of this national awareness campaign. METHODS: Data from the Children's Hospital of Eastern Ontario available in the Canadian Hospitals Injury Reporting and Prevention Program database were used to calculate the yearly incidence density of tap water scalds among children younger than 15 years in the city of Ottawa. RESULTS: It was found that there was no statistically significant change in the rate of pediatric tap water scalds following the national campaign, and that the rate of these injuries was already very low (3.73 per 100,000 person-years over the study period). Of these, only 17% required observation or admission to hospital. CONCLUSIONS: Given the low incidence of these injuries, their priority as a public health concern needs to be re-evaluated. If they continue to be a priority, new preventive strategies need to be used. It is thought that resources used to lobby for legislation of lower hot water temperatures may be more effective in reducing the incidence of these injuries.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".