The effect of prescribed exercise volume on biomarkers of chronic stress in postmenopausal women: Results from the Breast Cancer and Exercise Trial in Alberta (BETA)
Bibliographic record
Abstract
There is epidemiologic and biologic evidence for a role of stress in breast cancer etiology and physical activity mitigates the negative effects of stress. We examined the potential for a dose-response relationship between two volumes of aerobic exercise and biomarkers of chronic stress in post-menopausal women. The Breast Cancer and Exercise Trial in Alberta is a randomized controlled trial with post-menopausal women randomized to either a MODERATE (150 min per week) or HIGH (300 min per week) volume of exercise over a one year intervention period. Fasting serum concentrations of cortisol, cortisone, corticosterone and 11-deoxycortisol at baseline, 12 months (the end of the intervention), and 24 months. Intention-to-treat analyses were performed using general linear models, adjusted for baseline biomarker concentrations. There were modest but non-statistically significant decreases in cortisol (HIGH: -4%, 95% CI: -7%, 2%; MODERATE: -1%, 95%: CI: -14%, 4%) and corticosterone (HIGH: -4%, 95% CI: -12%, 6%; MODERATE: -5%, 95% CI: -14%, 4%) concentrations for both exercise groups between baseline and 12 months, and no difference in cortisone concentrations. Intention-to-treat analysis of 386 (97%) participants showed no statistically significant group differences for changes in biomarker levels at 12 months. Between baseline and 12 months, there were no differences in cortisol or cortisone and, at 24 months all stress hormone levels increased to near-baseline levels with no significant differences between the two intervention groups.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".