Study of mortality and cancer incidence in Xstrata's Ontario nickel workers : history, results, impact, and recommendations / by Bradley Gottfred.
Bibliographic record
Abstract
OBJECTIVES: Xstrata is a global diversified mining group whose businesses maintain a meaningful position in seven major international commodity markets, including those of copper and nickel, with a large cohort of nickel workers employed in the Province of Ontario, Canada at Sudbury in northeastern Ontario. Operating since 1929, Sudbury operations have historically included underground, milling, and smelting related to the \nproduction of nickel, copper, cobalt and other precious metals. \nThe objective for this study is to: follow-up and examine cancer incidence and mortality for various diseases in this occupational cohort \nMethods: This study will describe a retrospective occupational cohort study of \nmortality (1964-2001) and cancer incidence (1964-2001) conducted for Xstrata Nickel?s Ontario male nickel workers (n= 10,253 males). The cohort was originally assembled by researchers at McMaster University, with responsibility transferred, to the Northeastern Ontario Regional Cancer Centre of the Sudbury Regional Hospital in the late 1990s. Company nominal role and work history information were linked to provincial health data at Cancer Care Ontario. Given minimal out of province migration, using the Ontario population as a reference, standardized mortality ratios for a wide variety of diseases and standardized cancer incidence ratios were calculated overall, by start decade, by work area, by duration of employment, and by work area and duration of employment and by work area and start decade. \nRESULTS: In the cohort of male workers, there were 1,984 (19.35%) deaths and 1,127 (10.99%) incident cancers. While the results reflected very few significantly high SERs or SMRs, notable data was observed in deaths resulting from accidents, poisonings, or violence as both workers with less than 15 years since first hire (SIR=133,95% Cl: 111-158) and workers with 15 or more years since first hire (SIR=123,95% Cl: 104-144) displayed significantly high results. Notable data was also seen in workers with less than 15 years since first hire, with SMRs for rail, road, or air (SMR=136,95% Cl: 102-177) and possibly job-related (SMR=241, 95% Cl: 159-351) significantly high. \nCONCLUSIONS: There was no significant overall increase displayed for cancer incidence. Overall mortality displayed significant increases in deaths resulting from accidents, poisonings, or violence as well as deaths resulting firom rail, road, or air.
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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".