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Record W2089036820 · doi:10.1002/ajim.10023

Municipal firefighter exposure groups, time spent at fires and use of self‐contained‐breathing‐apparatus

2001· article· en· W2089036820 on OpenAlex

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.

Bibliographic record

VenueAmerican Journal of Industrial Medicine · 2001
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Performance
Canadian institutionsQueen's UniversityUniversité du Québec
FundersH2020 European Research Council
KeywordsMedicineFirefightingEnvironmental healthToxicologyPoison controlOccupational safety and healthOccupational exposureVentilation (architecture)Environmental scienceMeteorologyPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Previous studies have found significant associations between firefighting and cancer. METHODS: Fires, vehicle movement, and firefighter job assignment were determined, and storage and distribution of self-contained-breathing-apparatus (SCBAs) were tracked for 12 months. Time spent at fires and use of SCBAs were calculated. RESULTS: Only 66% of fire department personnel were 1st-line combat firefighters. Number of runs was an unreliable surrogate for time spent at fires. Eight firefighter exposure groups were identified (based on job title, firehall assignment, and time spent at fires), ranging from no exposures to 3,244 min/year/firefighter. SCBAs appear to have been used for approximately 50% of the time at structural fires but for only 6% of the time at all fires. CONCLUSIONS: Failure of previous studies to identify homogeneous exposure groups may have resulted in misclassification and underestimates of health risks. The approach used in this study may be used in epidemiological studies to identify exposure/response relationships.

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)0.001
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 score0.428
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.100
GPT teacher head0.393
Teacher spread0.293 · 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