RETRACTED: Scottish Firefighters Occupational Cancer and Disease Mortality Rates: 2000-2020
Post-publication record
OpenAlex flags this work as retracted, but it carries no matching Retraction Watch record in this frame.
Bibliographic record
Abstract
BACKGROUND: Increased mortality from cancers and other diseases has been reported in USA, Canadian, and Nordic firefighters. However, UK firefighters are understudied. AIMS: To determine whether UK firefighters suffer increased mortality from cancers and other diseases when compared with the general population. METHODS: Mortality from cancer and other diseases in Scottish male firefighters between 2000 and 2020 was compared with the general Scottish male population and expressed as standardized mortality ratios (SMRs) (with 95% confidence intervals, CI). RESULTS: Significant overall excess cancer mortality was found for Scottish firefighters compared with the general population (SMR 1.61, CI 1.42-1.81). Scottish firefighters were nearly three times more likely to die of malignant neoplasms (unspecified sites) (SMR 2.71, CI 1.71-4.00). Excess cancer mortality was also found for several site-specific cancers, including prostate (SMR 3.80, CI 2.56-5.29), myeloid leukaemia (SMR 3.17, CI 1.44-5.58), oesophagus (SMR 2.42, CI 1.69-3.29) and urinary system (kidney and bladder) (SMR 1.94, CI 1.16-2.91). Mortality from neoplasms of unknown behaviour was over six times greater in Scottish firefighters (SMR 6.37, CI 2.29-12.49). Additionally, significantly higher mortality was found for: acute ischaemic heart diseases (SMR 5.27, CI 1.90-10.33), stroke (SMR 2.69, CI 1.46-4.28), interstitial pulmonary diseases (SMR 3.04, CI 1.45-5.22), renal failure (SMR 3.28, CI 1.18-6.44) and musculoskeletal system diseases (SMR 5.64, CI 1.06-13.83). CONCLUSIONS: UK firefighters suffer significant excess mortality from cancer and other diseases when compared with the general population. Preventative health monitoring and presumptive legislation are urgently required to protect UK firefighters' health.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.011 |
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".