Association of Obesity and Cancer Risk in Canada
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The authors conducted a population-based, case-control study of 21,022 incident cases of 19 types of cancer and 5,039 controls aged 20-76 years during 1994-1997 to examine the association between obesity and the risks of various cancers. Compared with people with a body mass index of less than 25 kg/m(2), obese (body mass index of > or = 30 kg/m(2)) men and women had an increased risk of overall cancer (multivariable adjusted odds ratio = 1.34, 95% confidence interval (CI): 1.22, 1.48), non-Hodgkin's lymphoma (odds ratio = 1.46, 95% CI: 1.24, 1.72), leukemia (odds ratio = 1.61, 95% CI: 1.32, 1.96), multiple myeloma (odds ratio = 2.06, 95% CI: 1.46, 2.89), and cancers of the kidney (odds ratio = 2.74, 95% CI: 2.30, 3.25), colon (odds ratio = 1.93, 95% CI: 1.61, 2.31), rectum (odds ratio = 1.65, 95% CI: 1.36, 2.00), pancreas (odds ratio = 1.51, 95% CI: 1.19, 1.92), breast (in postmenopausal women) (odds ratio = 1.66, 95% CI: 1.33, 2.06), ovary (odds ratio = 1.95, 95% CI: 1.44, 2.64), and prostate (odds ratio = 1.27, 95% CI: 1.09, 1.47). Overall, excess body mass accounted for 7.7% of all cancers in Canada-9.7% in men and 5.9% in women. This study provides further evidence that obesity increases the risk of overall cancer, non-Hodgkin's lymphoma, leukemia, multiple myeloma, and cancers of the kidney, colon, rectum, breast (in postmenopausal women), pancreas, ovary, and prostate.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it