Components of the healthy eating index in nutrition of adult females
Bibliographic record
Abstract
To assess and monitor the nutriton and dietary status, the U.S. Department of Agriculture developed the Healthy Eating Index - HEI. The index consists of 10 components, each representing different aspects of a healthful diet. The aim of the study was to evaluate the nutrition in adult females and to analyze the actual nutrition according to selected four components (no. 6-9) of the Healthy Eating Index. Components 6 and 7 measure total fat and saturated fat consumption, respectively, as a percentage of total food intake (maximal 30 % and 10 % of total energy daily content respectively; in case of 31,3 % and 58,62 % females respectively). Components 8 and 9 measure total cholesterol (daily maximal 300 mg in case of 69,54 % participants) and sodium intake (maximal 2400 mg a day in case of 22,99 % probands).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".