In women, increased dietary antioxidants are associated with reduced risk of developing heart failure
Bibliographic record
Abstract
Commentary on Rautiainen S, Levitan EB, Mittleman MA, et al. Total antioxidant capacity of diet and risk of heart failure: a population-based prospective cohort of women. Am J Med 2013;126:494–500.[OpenUrl][1][CrossRef][2][PubMed][3] Heart failure is a syndrome comprising symptoms such as breathlessness alongside objective evidence of cardiac dysfunction. This is a common condition with a considerable economic impact on health services.1 Nutritional intake and status appear to be important in heart failure. Non-intentional weight loss in the setting of heart failure (cardiac cachexia) is an independent predictor of … [1]: {openurl}?query=rft.jtitle%253DAm%2BJ%2BMed%26rft.volume%253D126%26rft.spage%253D494%26rft_id%253Dinfo%253Adoi%252F10.1016%252Fj.amjmed.2013.01.006%26rft_id%253Dinfo%253Apmid%252F23561629%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1016/j.amjmed.2013.01.006&link_type=DOI [3]: /lookup/external-ref?access_num=23561629&link_type=MED&atom=%2Febnurs%2F17%2F3%2F72.atom
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".