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Record W4285240275 · doi:10.1088/0026-1394/59/1a/08006

Key comparison study on peptide purity - glycated hexapeptide of HbA1c

2022· article· en· W4285240275 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMetrologia · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadioactive Decay and Measurement Techniques
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMutual recognitionAmino acid analysisMetrologyCharacterization (materials science)Mass fractionChemistryChromatographyAnalytical Chemistry (journal)Materials scienceMathematicsNanotechnologyAmino acidStatisticsBiochemistryBusiness

Abstract

fetched live from OpenAlex

Main text Under the auspices of the Protein Analysis Working Group (PAWG) of the Comité Consultatif pour la Quantité de Matière (CCQM) a key comparison, CCQM-K115.c, was coordinated by the Bureau International des Poids et Mesures (BIPM), the Health Sciences Authority (HSA) of Singapore and the Chinese National Institute of Metrology (NIM). Nine Metrology Institutes or Designated Institutes and the BIPM participated. Participants were required to assign the mass fraction of the glycated hexapeptide of HbA1c (GE) present as the main component in the comparison sample for CCQM-K115.c. The comparison samples were prepared by HSA/BIPM from synthetic GE purchased from a commercial supplier and used as provided without further treatment or purification. GE was selected to be representative of the performance of a laboratory's measurement capability for the purity assignment of chemically synthesized peptides of known sequence, without cross-links, up to 5 kDa and modification (mono-glycation). It was anticipated to provide an analytical measurement challenge representative for the value-assignment of compounds of broadly similar structural characteristics. The majority of participants used amino acid analysis (PICAA) or quantitative nuclear magnetic resonance (PICqNMR) spectroscopy with a correction for structurally-related peptide impurities approach as the amount of material that has been provided to each participant (25 mg) is insufficient to perform a full mass balance based characterization of the material by a participating laboratory. The coordinators, the BIPM, the HSA and the NIM, were the laboratories to use the mass balance approach as they had more material available. It was decided to propose KCRVs for both the GE mass fraction and the mass fraction of the peptide-related impurities as indispensable contributor regardless of the use of PICAA, PICqNMR or mass balance to determine the GE purity. This allowed participants to demonstrate the efficacy of their implementation of the approaches used to determine the GE mass fraction. In particular, it allows participants to demonstrate the efficacy of their implementation of peptide-related impurity identification and quantification. More detailed studies on the identification/quantification of peptide-related impurities revealed that the integrity of the impurity profile of the related peptide impurities obtained by the participant is crucial for the impact on accuracy of the GE mass fraction assignment. The assessment of the mass fraction of peptide impurities is based on the assumption that that all results are directly taken for the calculation of the KCRVPepImp by use of random-effects meta-analysis (DerSimonian-Laird (DSL) variance-weighted mean). The KCRVPepImp of 45.4 mg/g is associated with a corresponding expanded uncertainty of 9.5 mg/g (k =2.26) providing a more realistic basis of evaluation for the capabilities of the participants to identify/quantify peptide-related impurities. Inspection of the degree of equivalence plots for the mass fraction of peptide impurities and additional information obtained from the peptide-related impurity profile indicates that in most cases the major related peptide impurities have been identified and quantified. The approach selected to obtain a KCRVGE for the mass fraction of GE is based on the DerSimonian-Laird (DSL) variance-weighted mean. The DSL mean takes into account the uncertainties of the results while introducing sufficient excess variance to allow for their observed dispersion resulting in a larger expanded uncertainty U(KCRVGE). The KCRVGE for CCQM-K115.c is 628 mg/g with a corresponding expanded uncertainty of the KCRVGE of 27 mg/g (k =2.26). All GE mass fraction results are in agreement with the KCRVGE. To reach the main text of this paper, click on Final Report . Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/ . The final report has been peer-reviewed and approved for publication by the CCQM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).

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.

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 score0.188
Threshold uncertainty score0.706

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.304
Teacher spread0.263 · 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