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Record W2738868183 · doi:10.5740/jaoacint.17-0183

Interlaboratory Comparison for the Determination of 24,25-Dihydroxyvitamin D3 in Human Serum Using Liquid Chromatography with Tandem Mass Spectrometry

2017· article· en· W2738868183 on OpenAlexaff
Stephen A. Wise, Susan S.-C. Tai, Michael A Nelson, Carolyn Q Burdette, Johanna E Camara, Andrew N. Hoofnagle, Thomas J. Laha, Graham D. Carter, Julia C. Jones, Emma L. Williams, Zoe Barclay, Glenville Jones, Martin Kaufmann, Neil Binkley, Amita Kapoor, Toni E. Ziegler, Kevin D. Cashman, Kirsten G. Dowling, Christopher T. Sempos

Bibliographic record

VenueJournal of AOAC International · 2017
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsQueen's University
FundersNational Institute of Standards and TechnologyCenters for Disease Control and Prevention
KeywordsChromatographyIsotope dilutionNISTDerivatizationChemistryLiquid chromatography–mass spectrometryTandem mass spectrometryMass spectrometryCalcifediolAnalytical Chemistry (journal)Computer scienceCalcitriol

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.217
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.379
Teacher spread0.338 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2017
Admission routes1
Has abstractyes

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