Occupations Associated With Poor Cardiovascular Health in Women
Bibliographic record
Abstract
INTRODUCTION: Research on the effect of occupation on cardiovascular health (CVH) among older women is limited. METHODS: Each of the seven American Heart Association's CVH metrics was scored as ideal (1) or non-ideal (0) and summed. Multivariable logistic regression was used to estimate the odds of poor overall CVH (CVH score of 0 to 2) comparing women employed in each of the top 20 occupational categories to those not employed in that category, adjusting for age, marital status, and race/ethnicity. RESULTS: (1) Bookkeeping, accounting, and auditing clerks; (2) first-line supervisors of sales workers; (3) first-line supervisors of office and administrative support workers; and (4) nursing, psychiatric, and home health aides were more likely to have poor overall CVH compared to women who did not work in these occupations. CONCLUSIONS: Several commonly held occupations among women were associated with poor CVH.
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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 | 0.000 | 0.001 |
| 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) | 0.004 | 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".