Vitamin D, neurocognitive functioning and immunocompetence
Bibliographic record
Abstract
PURPOSE OF REVIEW: Vitamin D deficiency is recognized as one of the most common medical conditions in children and adults. The major causes are inadequate sun exposure and inadequate intakes of dietary and supplemental vitamin D. Vitamin D deficiency and insufficiency defined as a 25-hydroxyvitamin D level less than 20 and 21-29 ng/ml, respectively, have been linked to increased risk for a variety of medical conditions including cancer, heart disease, type II diabetes, infectious diseases, autoimmune diseases, metabolic bone diseases and neurological disorders. RECENT FINDINGS: The skeletal muscle and brain have a vitamin D receptor and the central nervous system has a capacity to activate vitamin D. Low vitamin D status has been linked to poor performance in neurocognitive testing in elderly. Vitamin D deficiency has been associated with muscle weakness, depression, schizophrenia, Alzheimer's disease, multiple sclerosis and a lower motor neuron-induced muscle atrophy. SUMMARY: Correcting vitamin D deficiency and preventing vitamin D deficiency in children and adults should be a high priority for healthcare professionals to reduce risk for a wide variety of neurological disorders. Children and adults should take at least 400 international unit IU and 2000 IU vitamin D/day, respectively, to prevent vitamin D deficiency and insufficiency.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".