Additional file 1 of Relationship between diet quality scores and the risk of frailty and mortality in adults across a wide age spectrum
Bibliographic record
Abstract
Additional file 1: Table S1. Dietary variables included in calculations of the dietary scores. Table S2. 36-item frailty index. Table S3. Association of participants’ baseline characteristics with frailty, using univariate linear regression analyses and with mortality risk, using Cox regression analysis. Table S4. Correlation of the Nutrition Index-nutrient and Nutrition Index-lab/exam with other dietary scores. Table S5. Relationship of the Nutrition Index-nutrient and Nutrition Index-lab/exam with frailty, using multivariable-adjusted ordinary least squares regression analyses. Table S6. Relationship of the Nutrition Index-nutrient and Nutrition Index-lab/exam with mortality, using multivariable-adjusted Cox regression analysis. Table S7. Coefficients and p values for the 3-way interactions of each dietary score with age and sex on frailty. Table S8. Coefficients and p values for the 4-way interactions of each dietary score with age, sex, and frailty on mortality.
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 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 | 0.001 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.844 | 0.095 |
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".