# 2005 British Occupational Hygiene Society Published by Oxford University Press doi:10.1093/annhyg/mei001 Mortality from Lung and Kidney Disease in a Cohort of North American Industrial Sand Workers: An Update
Bibliographic record
Abstract
tionship between quartz exposure and death from both silicosis and lung cancer, after allowance for cigarette smoking and in the absence of known occupational carcinogens. Unexpectedly, a significant excess mortality from chronic non-malignant renal disease [observed 16; expected 7.6; standardized mortality ratio (SMR) 212] was also found, whereas deaths from renal cancer at this stage were close to expectation (observed 6; expected 5.2). Objectives: Our primary aim was to discover whether death from chronic renal disease was related to the estimated intensity of crystalline silica exposure. A further aim was to determine whether or not our previous estimates of lung cancer and silicosis risk were confirmed by mortality in the cohort 6 years later. Methods: With help from the US National Death Index, surviving members of the cohort, with the exception of employees of a small plant in Canada, were traced through 2000. The cause of death was determined for all who had died, for comparison against National and State mortality rates. Nested case-referent analyses were then undertaken, as previously, of deaths from lung cancer and silicosis, plus end-stage renal disease and kidney cancer, in relation to
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.105 | 0.039 |
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".