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Record W4311692827 · doi:10.1088/0026-1394/60/1a/08002

Key comparison study - organic solvent calibration solution - gravimetric preparation and value assignment of deoxynivalenol (DON) in acetonitrile (ACN)

2022· article· en· W4311692827 on OpenAlexaff
R D Josephs, Magali Bedu, A Daireaux, Z Guo, Xianjiang Li, Y Gao, Xiuqin Li, T Choteau, Gustavo Martos, Steven Westwood, Robert Wielgosz, Hongmei Li, M Simón, C Santana Smersu, Mariana Dingler Villarreal, M M Rzeznik, M Cirio, Eliane Cristina Pires do Rego, R Leal, L Carvalho, E Guimarães, Adilah Bahadoor, I Rajotte, Jennifer Bates, J E Melanson, L Morales Erazo, Susana Helena Arellano Ramirez, I Gonzalez, Désirée Prevoo-Franzsen, M Fernandes-Whaley, S Marbumrung, Pornnipa Jongmesuk, P Kankaew, K Shearman, C Boonyakong, T Gokcen, M Bilsel, Şükran Akkuş Özen, J Cea, O Martínez

Bibliographic record

VenueMetrologia · 2022
Typearticle
Languageen
FieldChemistry
TopicAnalytical Chemistry and Chromatography
Canadian institutionsNational Research Council CanadaMétis National Council
Fundersnot available
KeywordsMutual recognitionMetrologyCalibrationGravimetric analysisEnvironmental scienceTraceabilityMeasurement uncertaintyProcess engineeringComputer scienceMathematicsStatisticsChemistryEngineeringBusiness

Abstract

fetched live from OpenAlex

Main text The CCQM-K154.c comparison was coordinated by the the Bureau International des Poids et Mesures (BIPM) and the Chinese National Institute of Metrology (NIM) on behalf of the Organic Analysis Working Group (OAWG) of the Comité Consultatif pour la Quantité de Matière (CCQM) for National Measurement Institutes (NMIs) and Designated Institutes (DIs) which provide measurement services in organic analysis under the 'Comité International des Poids et Mesures' Mutual Recognition Arrangement (CIPM MRA) and/or have participated in the BIPM's Mycotoxin Metrology Capacity Building and Knowledge Transfer (MMCBKT) project as part of its "Metrology for Safe Food and Feed in Developing Economies" Capacity Building Programme. Gravimetrically-prepared solutions having an assigned mass fraction of specified organic analytes are routinely used to calibrate measurement processes for the quantification of the same analytes in matrix samples. Appropriate assignments of the property value and associated uncertainty of calibration solutions thus underpin the traceability of routine analysis and are critical for accurate measurements. Evidence of successful participation in relevant international comparisons is needed to document calibration and measurement capability claims (CMCs) made by national metrology institutes and designated institutes. In total, nine NMIs/DIs participated in the Track C, Model II, Key Comparison CCQM-K154.c [Gravimetric preparation and value assignment of deoxynivalenol (DON) in acetonitrile (ACN)] for emerging areas of global interest and innovation. Participants were requested to gravimetrically prepare calibration solutions and value assign the mass fractions, expressed in mg/kg, of deoxynivalenol (DON) in the acetonitrile (ACN) solution. Study samples, with assigned values and associated uncertainties were prepared by the comparison participants and sent to the coordinating laboratory for comparison. The Key Comparison Reference Values (KCRVs), calculated from values measured by the coordinating laboratory based on calibrations obtained from independent gravimetrically prepared calibrant solutions, agreed with participants reported values, within their stated uncertainties. DON belongs to the large group of trichothecene mycotoxins. It is produced by certain fungi of the genus Fusarium that predominantly infect wheat, corn, oats, barley, rice, and other grains in the field or during storage. It was anticipated to provide a challenge representative for the gravimetrical preparation and value assignment of calibration solutions in the mass fraction range of 10 mg/kg to 100 mg/kg of mycotoxins with broadly similar structural characteristics. Ten participants of the MMCBKT programme were provided with a stock solution having a known DON mass fraction and expanded uncertainty to use to gravimetrically prepare and value assign a calibration solution. Three NMIs/DIs also participated using their own calibration solutions. The use of in-house solutions required an additional capacity to undertake a fit-for-purpose purity assessment. NIM was the only NMI participating using both the MMCBKT based and their own in-house assigned solutions in order to connect the two different groups. It was decided to propose separate KCRVs for each of the two ampoules provided by the participating NMIs/DIs based on the DON mass fraction. This allowed participants to demonstrate the efficacy of their implementation of the approaches used to gravimetrically prepare calibration solutions and to assess the DON mass fraction. The majority of the DON mass fraction KCRVs ( w KCRV ) for CCQM-K154.c spanned a mass fraction range of 9.88 mg/kg to 123.45 mg/kg. The relative expanded uncertainties U( w KCRV ) ranged from 2.8 % to 6.8 %. Inspection of the degree of equivalence plots for the DON mass fraction assignments in CCQM-K154.c indicated that there was an excellent agreement of results. 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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.017
GPT teacher head0.268
Teacher spread0.251 · 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.

Study designBench or experimental
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".

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Citations1
Published2022
Admission routes1
Has abstractyes

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