TITLE: Vitamin D Supplementation in Long-Term Care Residents: A Review of the Clinical Effectiveness and Guidelines
Bibliographic record
Abstract
Vitamin D is generic term that is used to refer to a number of fat soluble compounds that affect calcium and phosphorus balance and bone metabolism. 1,2 One form of vitamin D is synthesized in the body when the skin is exposed to ultraviolet light or sunlight, which promotes the conversion of a precursor of vitamin D to vitamin D3 (cholecalciferol). 1,2 Dietary vitamin D2 (ergocalciferol) is another source of vitamin D and is found in foods such as fish, eggs, fortified milk, and cod liver oil. 1,3 Both ergocalciferol and cholecalciferol must be converted to the physiologically active form of vitamin D via metabolic processes in the liver and kidneys. 1,2 Vitamin D deficiency can arise from limited sun exposure, impaired ability of the liver or kidneys to activate vitamin D, limited dietary intake, or poor absorption from the intestine. 1,2 Vitamin D deficiency can cause osteomalacia (characterized by weakness of the bone and muscle), contribute to the development of osteoporosis, immune system dysfunction, and bone pain and is also associated with an increased risk of falls and higher risk of fractures in older adults. 1,2 Evidence suggests that vitamin D deficiency is common amongst residents of long-term care (LTC) facilities, 4 with measured vitamin D levels reported as insufficient or deficient in as many as 51 % of residents. 5 Health Canada recommends a supplement of 600 IU units of vitamin D
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".