Populating an Indicator of Serious Paediatric Fall Injuries across Age and Public Health Units in Ontario
Bibliographic record
Abstract
Fall injuries among children and youth represent a significant burden to public health. Currently, there is no indicator assessing serious fall injuries in children. The purpose of this study was to populate an indicator of serious fall injuries within the paediatric population (0-19 years) using existing ICD-10 coded hospitalization data. The Discharge Abstract Database was used to examine all fall-related hospitalizations in Ontario from 2010-2019. Rates per 100,000 population and rate ratios were calculated for all fall-related and serious fall injuries; serious falls accounted for 3,652 hospitalizations. The highest rates for all fall-related and serious fall injuries were reported in rural health units. The mechanisms of serious fall injuries were highest among males 10-14 and 15-19 from skis, blades, skates, and boards, whereas rates were highest among females 0-4 from stairs and 5-9 from playgrounds. This indicator can be used to prompt action to reduce serious fall injuries in children.
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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 | 0.001 |
| Bibliometrics | 0.003 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".