PERCEIVED BENEFITS AND BARRIERS TO AN INPATIENT EXERCISE INTERVENTION FOR RECENTLY TREATED ADULTS WITH ACUTE LEUKEMIA: PRELIMINARY RESULTS
Bibliographic record
Abstract
Objective: Investigate the prevalence of metabolic syndrome (MetS) according to sex and female parity in IMIAS (N=1719). Methods: Adjusting for participant age and education, we used Poisson regression to calculate the prevalence ratios (PR) of MetS in men compared to nulliparous and parous women. Results: Prevalence of MetS was 26% for men, 27% for nulliparous women, and 42% for parous women. Women from Tirana and Natal had significantly greater prevalence of MetS than men (PR 1.88, 95%CI 1.36-2.59; PR 2.31, 95%CI 1.57-3.39, respectively). No difference between the sexes was observed elsewhere. Prevalence of MetS was similar for men and nulliparous women, except in Brazil where all women had greater prevalence of MetS than men. In Albania, the prevalence of MetS was significantly greater in parous women compared to men/nulliparous women (PR 1.95 95%CI 1.41-2.70). Conclusions: Parity may partially explain excess prevalence of MetS in women from Albania, but not Brazil.
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.
How this classification was reachedexpand
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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".