MétaCan
Menu
Back to cohort
Record W3212896352 · doi:10.33137/utjph.v2i2.37006

Current diesel engine exhaust exposure in the Ontario construction industry

2021· article· en· W3212896352 on OpenAlex
Stephanie Ziembicki, Tracy L Kirkham, Paul A. Demers, Cheryl Peters, Melanie Gorman-Ng, Hugh Davies, Thomas Tenkate, Sheila Kalengé, Nicola Blagrove-Hall, Kate Jardine, Victoria H Arrandale

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueUniversity of Toronto Journal of Public Health · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicAir Quality and Health Impacts
Canadian institutionsWorld Wildlife Fund CanadaUniversity of CalgaryAlberta Health ServicesOccupational Cancer Research CentreUniversity of British ColumbiaPublic Health OntarioToronto Metropolitan UniversityUniversity of Toronto
Fundersnot available
KeywordsOccupational exposure limitDiesel exhaustOccupational exposureEnvironmental scienceEnvironmental healthDiesel engineExposure assessmentDiesel fuelInhalation exposureConstruction industryParticulatesToxicologyWaste managementEngineeringEnvironmental engineeringMedicineChemistryAutomotive engineeringInhalation

Abstract

fetched live from OpenAlex

Introduction: Diesel engine exhaust (DEE) is a known carcinogen and a common occupational exposure in Canada, particularly within construction. The use of diesel-powered equipment in the construction industry is widespread, but little is known about DEE exposures and occupational disease in this work setting. The objective of this study was to characterize and identify key determinants of DEE exposure at construction sites in Ontario.
 Methods: Diesel particulate matter (DPM) measurements were taken from workers employed on seven infrastructure construction worksites in Ontario. Full-shift personal air samples were collected from workers using a constant-flow pump and SKC aluminum cyclone with 37-mm quartz fibre filters in an open-faced cassette. Samples were analyzed for elemental carbon (EC), a surrogate of DEE exposure, following NIOSH method 5040. Exposures were compared to recommended health-based limits, including the Dutch Expert Committee on Occupational Safety (DECOS) limit (1.03µg/m3 respirable EC) and the Finnish Institute of Occupational Health (FIOH) recommendation (5µg/m3 respirable EC). A determinants of exposure model was constructed.
 Results: In total, 126 DPM samples were collected, ranging from <0.47-52.58µg/m3 with a geometric mean (GM) of 4.23µg/m3 (geometric standard deviation (GSD)=3.05). Overall, 44.8% of samples exceeded the FIOH limit, mostly within underground worksites (93.5%), and 88.8% exceeded the DECOS limit. Underground workers (GM=13.20µg/m3, GSD=1.83) had exposures approximately 4-times higher than below grade workers (GM=3.56µg/m3, GSD=1.94) and 9-times higher than aboveground workers (GM=1.49µg/m3, GSD=1.75). Work grade, enclosed cabs, and seasonality were identified as the major determinants of exposure.
 Conclusions: This study provides a better understanding of current DPM exposure in Canadian construction. Most exposures were above recommended health-based limits, signifying a need to further reduce DPM levels in construction. These results can inform a hazard reduction strategy including a new occupational exposure limit and targeted intervention/control measures to reduce DPM exposure and the burden of occupational cancer.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.339
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.069
GPT teacher head0.288
Teacher spread0.219 · 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