An updated study of mortality among North American synthetic rubber industry workers
Bibliographic record
Abstract
AIM: This study evaluated the mortality experience of workers from the styrene-butadiene industry. METHODS: The authors added seven years of follow up to a previous investigation of mortality among 17 924 men employed in the North American synthetic rubber industry. Analyses used the standardised mortality ratios (SMRs) to compare styrene-butadiene rubber workers' cause specific mortality (1943-98) with those of the United States and the Ontario general populations. RESULTS: Overall, the observed/expected numbers of deaths were 6237/7242 for all causes (SMR = 86, 95% CI 84 to 88) and 1608/1741 for all cancers combined (SMR = 92, 95% CI 88 to 97), 71/61 for leukaemia, 53/53 for non-Hodgkin's lymphoma, and 26/27 for multiple myeloma. The 16% leukaemia increase was concentrated in hourly paid subjects with 20-29 years since hire and 10 or more years of employment in the industry (19/7.4, SMR = 258, 95% CI 156 to 403) and in subjects employed in polymerisation (18/8.8, SMR = 204, 95% CI 121 to 322), maintenance labour (15/7.4, SMR = 326, 95% CI 178 to 456), and laboratory operations (14/4.3, SMR = 326, 95% CI 178-546). CONCLUSION: The study found that some subgroups of synthetic rubber workers had an excess of mortality from leukaemia that was not limited to a particular form of leukaemia. Uncertainty remains about the specific agent(s) that might be responsible for the observed excesses and about the role of unidentified confounding factors. The study did not find any clear relation between employment in the industry and other forms of lymphohaematopoietic cancer. Some subgroups of subjects had more than expected deaths from colorectal and prostate cancers. These increases did not appear to be related to occupational exposure in the industry.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".