Salt, processed meat and the risk of cancer
Bibliographic record
Abstract
This study assesses the association between salt added at the table, processed meat and the risk of various cancers. Mailed questionnaires were completed by 19 732 patients with histologically confirmed incident cancer of the stomach, colon, rectum, pancreas, lung, breast, ovary, prostate, testis, kidney, bladder, brain, non-Hodgkin's lymphoma or leukaemia, and 5039 population controls,between 1994 and 1997. Measurement included information on socioeconomic status, lifestyle habits and diet. A 69-item food frequency questionnaire provided data on eating habits 2 years before the study. Odds ratios and 95% confidence intervals were derived through unconditional logistic regression. Compared with never adding salt at the table, always or often adding salt at the table was associated with an increased risk of stomach, lung, testicular and bladder cancer. Processed meat was significantly related to the risk of the stomach, colon, rectum, pancreas, lung, prostate, testis, kidney and bladder cancer and leukaemia; the odds ratios for the highest quartile ranged from 1.3 to 1.7. The findings add to the evidence that high consumption of salt and processed meat may play a role in the aetiology of several cancers.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".