Respiratory Outcomes of Firefighter Exposures in the Fort McMurray Fire
Bibliographic record
Abstract
OBJECTIVE: Determine effects on respiratory health of firefighters attending a catastrophic wildfire. METHODS: Within the Alberta Administrative Health Database, we identified five community-based controls for each firefighter in a cohort of 1234 deployed to the 2016 Fort McMurray fire. Spirometry records were identified and a stratified sample assessed clinically. We estimated PM2.5 particles exposure. RESULTS: Firefighters had an increased risk of asthma consultation post-fire (OR new onset asthma = 2.56; 95%CI 1.75 to 3.74). Spirometry showed decreased FEV1 and FVC with increasing exposure. In the clinical assessment, 20% had a positive MCT and 21% BWT. Those with ongoing fire-related symptoms had a higher concurrence of positive MCT and BWT (OR = 4.35; 95%CI 1.11 to 17.12). Lower diffusion capacity related to higher exposure. CONCLUSIONS: Massive exposures during a wildfire are associated with non-resolving airways damage.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".