<scp>UK</scp> Nutrition Research Partnership ‘Hot Topic’ workshop: Vitamin D—A multi‐disciplinary approach to (1) elucidate its role in human health and (2) develop strategies to improve vitamin D status in the <scp>UK</scp> population
Bibliographic record
Abstract
Vitamin D is truly unique-not a 'vital' amine in the true sense of the word, but rather a prohormone, which is produced in the skin during exposure to sunlight (UVB radiation at 290-315 nm) and which can also be obtained from food and from supplements. A high prevalence of low vitamin D status has been reported across the world in a wide range of population groups, and this includes communities living in low latitude areas despite the abundance of sunlight. It is accepted that vitamin D status is reflected by the level of the circulating metabolite 25-hydroxyvitamin D (25[OH]D), which is produced by hepatic hydroxylation of vitamin D, derived either from the skin from UV exposure or the gut from oral intake. Vitamin D has been associated with a wide range of health outcomes, but controversies remain as to their exact nature and extent and whether associations are in the causal pathway. In order to enable wider discussions on this nutrient, a 'Hot Topic' Vitamin D Workshop achieved funding from the UK Nutrition Research Partnership Medical Research Council call. The objectives of the workshop were (1) to elucidate the role of vitamin D in human health and (2) develop strategies to improve vitamin D status in the UK population. This paper provides a detailed resume of the discussions of the workshop; of the presentations and concomitant Q&As; and of identified areas for future research.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.088 | 0.024 |
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".