MétaCan
Menu
Back to cohort
Record W3172466539 · doi:10.1097/jom.0000000000002286

Respiratory Outcomes of Firefighter Exposures in the Fort McMurray Fire

2021· article· en· W3172466539 on OpenAlex
Nicola Cherry, James R. Barrie, Jeremy Beach, Jean‐Michel Galarneau, Trish Mhonde, Eric Wong

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Occupational and Environmental Medicine · 2021
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsSpirometryMedicineAsthmaCohortEnvironmental healthCohort studyInternal medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.098
GPT teacher head0.435
Teacher spread0.337 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it