Toluene diisocyanate occupational exposure data in the polyurethane industry (2005–2020): A descriptive summary from an industrial hygiene perspective
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.
Bibliographic record
Abstract
This article provides an overview of toluene diisocyanate (TDI) workplace air concentration data. Data were collected between 2005-2020 in workplaces across the United States, Canada, and the European Union by a number of different organizations, primarily using the sampling procedures published in OSHA Methods 42 and 5002. The data were then collated and organized by the International Isocyanate Institute. Air samples were collected from several market segments, with a large portion of the data (87%) from the flexible foam industry. The air samples (2534 in total) were categorized into “area” or “personal,” and the personal samples were subcategorized into “task,” “short term,” and “long term.” Most of the air sample concentrations (87%) were less than 5 ppb. However, the presence of airborne TDI greater than 5 ppb indicated the importance of respiratory protection in some situations; therefore, respirator use patterns were studied and summarized. Additionally, this article provides a summary of air sample concentrations at different flexible foam manufacturing job roles. The information on air sampling concentrations and respiratory protection during TDI applications collected in this paper could be useful for product stewardship and industrial hygiene purposes in the industries studied.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.019 | 0.007 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.071 | 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 it