Evidence of revising calcium Dietary Reference Intakes (DRIs) for Korean elderly
Bibliographic record
Abstract
Recently bone health is an important issue in public health aspect and calcium is the most critical nutrient to influence bone mass and bone mineral density, and consequently bone fracture. Calcium DRIs of Korea are much lower than those of US/Canada which have been revised recently. Since the requirement of calcium in Asians may be different from Caucasian, it would be desirable for Korean DRIs for calcium to be established by Korean data; however, little data of high quality exist. Based on 2008–2010 Korea National Health and Nutrition Examination Survey data, most women aged 65 and more have bone health problems such as osteoporosis and osteopenia. In women and men aged 65 and more, higher calcium intake was significantly associated with higher bone mineral density as well as lower incidence of osteoporosis. Means of the highest quartile calcium intake, which are 750 mg for women and 930mg for men, are much higher than the present Estimated Average Requirements (EAR) of elderly women and men, which are 570 mg and 560 mg, respectively. Therefore, it seems valid to increase calcium EAR for Korean elderly. (This research was supported by a fund(2012‐E35004–00) by Research of Korea Centers for Disease Control and Prevention)
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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 | 0.036 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".