Medical Monitoring for Occupational Asthma Among Toluene Diisocyanate Production Workers in the United States
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to describe a study of medical monitoring methods and lessons learned in detecting health outcomes in U.S. plants producing toluene diisocyanate (TDI). METHODS: A multidisciplinary team implemented a medical and environmental monitoring program in three TDI plants. RESULTS: Of 269 eligible workers, 197 (73%) participated and 42 (21%) met symptom and/or lung function criteria that would trigger evaluation for possible asthma over 5 years of data collection. Subsequent evaluation was delayed for most, and a web-based data collection system improved timeliness. CONCLUSION: Medical monitoring of TDI workers identified workers triggering further assessment per study protocol. Systems and/or personnel to ensure rapid follow-up are needed to highlight when triggering events represent potential cases of asthma needing further evaluation. Implementation of a research protocol requires resources and oversight beyond an occupational health program.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".