Bibliographic record
Abstract
The last couple of decades have seen an explosion in our interest and understanding of the role of vitamin D in the regulation of immunity. At the molecular level, the hormonal form of vitamin D signals through the nuclear vitamin D receptor (VDR), a ligand-regulated transcription factor. The VDR and vitamin D metabolic enzymes are expressed throughout the innate and adaptive arms of the immune system. The advent of genome-wide approaches to gene expression profiling have led to the identification of numerous VDR-regulated genes implicated in the regulation of innate and adaptive immunity. The molecular data infer that vitamin D signaling should boost innate immunity against pathogens of bacterial or viral origin. Vitamin D signaling also suppresses inflammatory immune responses that underlie autoimmunity and regulate allergic responses. These findings have been bolstered by clinical studies linking vitamin D deficiency to increased rates of infections, autoimmunity, and allergies. Our goals here are to provide an overview of the molecular basis for immune system regulation and to survey the clinical data from pediatric populations, using randomized placebo-controlled trials and meta-analyses where possible, linking vitamin D deficiency to increased rates of infections, autoimmune conditions, and allergies, and addressing the impact of supplementation on these conditions.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".