Severity of Burn Injury and the Relationship to Socioeconomic Status in Nova Scotia, Canada
Bibliographic record
Abstract
Objective. Few Canadian studies have examined the relationship between socioeconomic status (SES) and incidence of burn injury. We seek to evaluate this relationship using median income as a measure of SES in Nova Scotia, Canada.Methods. Nova Scotia residents admitted to the Queen Elizabeth II burn unit in Halifax, Nova Scotia, from 1995 to 2012, were included in the study. SES was estimated by linking the subject’s postal code to median family household income via Canadian population census data at the level of dissemination areas. Four equal income groups ranging from lowest to highest income quartile were compared (average total burn percentage). Likelihood ratio was calculated to evaluate the effect of median family income burn injury in each income quartile.Results. 302 patients were included in the analysis. Average percent total burn surface area was 19%, 15%, 15%, and 14% ( p=0.18 ) per income quartile (Q1: lowest, Q4: highest), respectively. Likelihood ratios for income quartile Q1–Q4 were 1.3 (0.8–1.6), 1.2 (0.6–1.4), and 0.7 (0.6–1.2), respectively.Conclusion. Contrary to findings in other geographic regions of the world, severity or incidence of burn injury in Nova Scotia, Canada, does not change in relation to SES when using family median income as a surrogate.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".