Central body fatness is a stronger predictor of cancer risk than overall body size
Bibliographic record
Abstract
Abstract The importance of body size versus weight distribution for cancer risk is unclear. We investigated associations between measures of body size and shape and the risk of developing cancer. The study population consisted of 26,607 participants from the Alberta’s Tomorrow Project cohort. Two main measures of body shape and size were examined: i) body mass index (BMI) and ii) waist circumference (WC). Incident cancers were identified via linkage to the Alberta Cancer Registry. Cox proportional hazards models were used. Males and females classified as obese (BMI ≥ 30 kg /m −2 ) have a 33% and 22% increased risk of all-cancer, respectively, than their normal weight counterparts. Similar all-cancer risk increases are observed for those above sex-specific WC guidelines. Mutual adjustment for WC attenuates the association between BMI and all-cancer risk, especially among females. Central adiposity appears to be a stronger predictor of all-cancer risk than body size.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".