Occupational Exposure to Diesel Exhaust in the Canadian Federal Jurisdiction
Bibliographic record
Abstract
To assess the impact of the proposed American Conference of Governmental Industrial Hygienists threshold limit value-time-weighted average to diesel particulate matter (DPM), 177 full-shift samples were taken in 23 workplaces under Canadian federal jurisdiction. National Institute for Occupational Safety and Health (NIOSH) Method 5040 (Elemental Carbon: Diesel Exhaust) was used to assess exposure. Quality control tests were conducted prior to field sampling by taking air samples in the exhaust stream of two diesel engines mounted on a test bed and having them analyzed by two laboratories using the same thermal program. Field sampling results indicated that 77% of the elemental carbon (EC) levels were below the currently proposed limit of 20 microg/m(3), and 54% below 10 microg/m(3). The geometric mean concentration of EC was 24.4 microg/m(3) in high-activity and 4.0 microg/m(3) in low-activity work sites. Corresponding arithmetic mean concentrations were 41.4 and 8.4 microg/m(3), respectively. The ratio of EC to total carbon (TC) was close to 90% for all quality control samples. It was no higher than 50% for the field samples, and it varied significantly with EC concentration. Finally, results are presented from the analysis of 41 samples by a third laboratory using a thermal-optical method slightly different from NIOSH 5040. Even if one were to opt for EC as a surrogate for DPM, unless analysis details (particularly the thermal program) are specified, significant differences in the results can be expected. This could lead to problems for regulatory agencies and for epidemiologic research.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".