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Record W2137426267 · doi:10.1080/714044193

Current Chemical Exposures Among Ontario Construction Workers

2003· article· en· W2137426267 on OpenAlexaffabout
Dave K. Verma, Lawrence A. Kurtz, Dru Sahai, Murray M. Finkelstein

Bibliographic record

VenueApplied Occupational and Environmental Hygiene · 2003
Typearticle
Languageen
FieldChemical Engineering
TopicChemical Safety and Risk Management
Canadian institutionsAlcohol Countermeasure Systems (Canada)McMaster University
Fundersnot available
KeywordsEnvironmental healthEnvironmental scienceOccupational exposureAsbestosExposure assessmentHazardous wasteWaste managementDiesel exhaustEnvironmental chemistryEnvironmental engineeringEngineeringDiesel fuelMedicineMetallurgyChemistryMaterials science

Abstract

fetched live from OpenAlex

Current occupational exposures to chemical agents were assessed as part of an epidemiological study pertaining to the cancer and mortality patterns of Ontario construction workers. The task-based exposure assessment involved members from nine construction trade unions. Air samples were taken using personal sampling pumps and collection media. A DustTrak direct-reading particulate monitor was also employed. Exposure assessments included measurements of airborne respirable, inhalable, total, and silica dust; solvents; metals; asbestos; diesel exhaust and man-made mineral fibers (MMMF). In total, 396 single- or multi-component (filter/tube), 798 direct-reading, and 71 bulk samples were collected. The results showed that Ontario construction workers are exposed to potentially hazardous levels of chemical agents. The findings are similar to those reported by other researchers, except for silica exposure. In our study, silica exposure is much lower than reported elsewhere. The difficulty associated with assessing construction workers' exposures is highlighted.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.185
Threshold uncertainty score0.372

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.007
GPT teacher head0.188
Teacher spread0.181 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations46
Published2003
Admission routes2
Has abstractyes

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