Occupational exposure to NDMA and NMor in the European rubber industry
Bibliographic record
Abstract
Many nitrosamines are suspected of being human carcinogens, with the highest concentrations in the environment being measured in the rubber industry. Time trends of personal exposure to N-nitrosodimethylamine (NDMA) and to N-nitrosomorpholine (NMor) during the past two decades in the German rubber industry were analysed and compared with cross-sectional studies in the same period in the Netherlands, Poland, the UK and Sweden. In the majority of the surveyed departments exposures reduced over time, but considerable heterogeneity was present between departments and sectors. Significant reductions were primarily found in curing and post-treating departments and ranged from -3% year(-1) to -19% year(-1). In contrast, NDMA levels increased (+13% year(-1)) in maintenance and engineering in the tyres industry. Average NDMA-levels in general rubber goods (GRG) and NMor-levels in tyre production in Germany did not decrease significantly in the past two decades, whereas NDMA-levels in tyre production (-10% year(-1)) and NMor-levels in GRG (-7% year(-1)) declined significantly after the introduction of an exposure limit for total nitrosamines in Germany in 1988. Confidence intervals of average exposures in other studied countries largely overlap trends observed in Germany. Exposure to N-nitrosamines decreased on average two-to-five fold in the German rubber industry with comparable concentration levels in other European countries. Although average levels are well below the current limits exposure has not been eliminated, and incidental high exposures do still occur.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".