Interlaboratory Comparison for the Determination of 24,25-Dihydroxyvitamin D3 in Human Serum Using Liquid Chromatography with Tandem Mass Spectrometry
Bibliographic record
Abstract
Six laboratories associated with the Vitamin D Standardization Program (VDSP) participated in an interlaboratory comparison of LC with tandem MS (MS/MS) methods for the determination of 24,25-dihydroxyvitamin D3 [24,25(OH)2D3] in human serum. The laboratories analyzed two different serum-based Standard Reference Materials (SRMs) intended for use in the determination of 25-hydroxyvitamin D and 30 samples from the Vitamin D External Quality Assessment Scheme (DEQAS). All laboratory methods for 24,25(OH)2D3 were based on isotope dilution LC-MS/MS; three of the methods used derivatization of the vitamin D metabolites before LC-MS/MS. Laboratory results were compared to the National Institute of Standards and Technology (NIST) results, which were obtained using their newly developed candidate reference measurement procedure for 24,25(OH)2D3. Laboratory results for the SRM samples varied in comparability to the NIST results, with one laboratory in excellent agreement (-1.6% mean bias), three laboratories at 10-15% mean bias, and the remaining laboratory at 36% mean bias. For the 30 DEQAS samples, the mean bias for the five laboratories ranged from 6 to 15%; however, the SD of the bias ranged from 8 to 29%. As a result of this intercomparison study, one laboratory discovered and corrected a method calculation error and another laboratory modified and improved their LC-MS/MS method.
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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 | 0.074 | 0.073 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".