Case‐control study of anthropometric measures and breast cancer risk
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
A population-based case-control study of 1,233 incident breast cancer cases and 1,241 controls was conducted in Alberta between 1995 and 1997 to examine the influence of anthropometric factors on the risk of breast cancer using several newly derived variables. Data on current height, weight and waist and hip circumference were collected by interviewers using standardized methods. Respondents recalled their body weight at each decade from age 20 to the referent year. Several variables were estimated, and unconditional logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs). No statistically significant associations for any of the estimated variables with breast cancer risk for premenopausal women (462 cases, 475 controls) were found. The results for postmenopausal women (771 cases, 762 controls) in the highest vs. lowest quartiles were, for waist circumference, OR = 1.30 (95% CI 0.97-1.73); waist-hip ratio, OR = 1.43 (95% CI 1.07-1.93); weight gain since age 20, OR = 1.35 (05% CI 1.01-1.81); difference between maximum and minimum weights over adult lifetime, OR = 1.56 (95% CI 1.16-2.08); and the reference weight minus the minimum weight since age 20, OR = 1.47 (95% CI 1.10-1.97). Statistically significant trends in risk were observed for these variables. Effect modification with hormone replacement therapy use was found for most variables assessed for postmenopausal women, with much stronger associations found among never-users compared to ever-users. We found strong evidence that waist-hip ratio and weight gained over lifetime, as assessed by different variables, are postmenopausal breast cancer risk factors. These effects were independent of dietary intake and lifetime total physical activity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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