Standardization of measurements of 25-hydroxyvitamin D3 and D2.
Bibliographic record
Abstract
The vitamin D status is increasingly assessed/monitored in different populations, research cohorts and individual patients. This is done by measuring the liver metabolites 25-hydroxyvitamin D3 and D2 as biomarkers. Recommendations for using specific serum concentrations of these biomarkers to assess a person's vitamin D status were done. This requires current vitamin D assays to be sufficiently accurate over time, location and laboratory procedures. In view of the fact that several studies demonstrated that current 25(OH)D measurement methods do not meet this prerequisite, standardization is needed. This paper rehearses the basic concept of standardization, in particular applied to measurements of 25-hydroxyvitamin D. Progress has been made by establishing a reference measurement system consisting of reference methods and reference materials. Coordinated efforts to improve the accuracy and standardize measurements are being performed by organizations such as the U.S. NIH, the CDC and Prevention, the NIST together with their national and international partners. Beyond describing the available reference measurement system and its use as calibration hierarchy to establish traceability of measurements with routine laboratory methods to the SI-unit, this report will also focus on other aspects considered essential for a successful and sustainable standardization, such as analytical issues related to the definition of the measurand and analytical performance goals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.057 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".