Ten-Year Epidemiological Study of Pediatric Burns in Canada
Bibliographic record
Abstract
The aim of this study was to report on the temporal trends, incidence rates, demographic, and external-cause data for all burn injury related deaths and hospital admissions among children Canadian aged 0 to 19 years for the years 1994 to 2003. Statistics Canada and Canadian Institute of Health Information data were used to describe burn injury related deaths and hospital admission trends in children aged 0 to 19 years who were residents of Canada (1994-2003). Population estimates were derived from census data provided by Statistics Canada. During the 10-year period, 494 children died and 10,229 were admitted to a Canadian hospital because of a burn-related injury. Males and children aged less than 5 years of age were at the highest risk of injury, with children aged 1 to 5 years at the highest risk of death. Scalds represented the major etiological factor contributing to thermal injuries accounting for 50% of all hospital admissions. Temporal trends indicate a significant a significant decline in burn injuries across all age groups during the period 1994 to 2003. There has been a clear reduction in the number of patients with burn injury requiring hospital admission. This trend indicates success in safety initiative to prevent burn injuries as well as in improvements in the treatments of burn and hospital admission procedures. Nonetheless, burn injury remains a serious threat to the well-being of the Canadian pediatric population.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".