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Record W4407155506 · doi:10.1088/0026-1394/62/1a/08010

Key comparison CCQM-K78.b - non-polar analytes in organic solvent: methoxychlor and trifluralin in acetonitrile

2025· article· en· W4407155506 on OpenAlexaff
Steven Westwood, R D Josephs, Tiphaine Choteau, Gustavo Gabriel Martos, Robert Wielgosz, Y Acho Sarzuri, Evelyn Mae T. Mendoza, Eliane Cristina Pires do Rego, Fernando Gustavo Marques Violante, W da Silva Souza, Lucas Silva Carvalho, João Fernandes, J. W. Bates, Isabelle Rajotte, Jeremy E. Melanson, H Li, Z Guo, Su Feng, S Wang, Ting Huang, Béatrice Lalerle, F Gantois, C Piechotta, R Philipp, Kamil Kamiński, Panagiota Giannikopoulou, E Skotidaki, E Kakoulides, C Pui-Kwan, Miho Kuroe, Naoki Itoh, Marco Antonio Ávila Calderón, L Regalado Contreras, M Arce Osuna, Mohammed Alrashed, Ting Li, Juan Wu, Cheow Pui Sze, Teo Tang Lin, L Quinn, Caitlin Swiegelaar, M Fernandes-Whaley, Sangdoo Ahn, Thitiphan Chaiphet, Nittaya Sudsiri, W Bellazreg, M Bilsel, Burcu Binici, Tabatha Hambidge, F Almirón, Giorgio Colombo

Bibliographic record

VenueMetrologia · 2025
Typearticle
Languageen
FieldChemistry
TopicAnalytical Methods in Pharmaceuticals
Canadian institutionsNational Research Council CanadaMétis National Council
Fundersnot available
KeywordsAcetonitrileMethoxychlorTrifluralinSolventPolarChemistryChromatographyOrganic chemistryPesticidePhysics

Abstract

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Main text The CCQM-K78.b key comparison was coordinated by the Bureau International des Poids et Mesures (BIPM) on behalf of the CCQM Organic Analysis Working Group (OAWG) of the 'Comité Consultatif pour la Quantité de Matière' (CCQM), for National Measurement Institutes (NMIs) and Designated Institutes (DIs) providing measurement services in organic analysis under the 'Comité International des Poids et Mesures' (CIPM) Mutual Recognition Arrangement (MRA). This key comparison was conducted as a 'Track A' comparison within the OAWG's 10-year strategic plan. The goal of CCQM-K78.b was to underpin capabilities for the value assignment of calibration solutions containing low polarity/non-polar organic analytes in organic solvents. The selected model system consisted of a two-component pesticide solution in acetonitrile, comprising methoxychlor and trifluralin. Participants were tasked with assigning the mass fractions, in units of μg/g, of methoxychlor and trifluralin in acetonitrile solution. The mass fraction levels and analytical challenges of the selected analytes were representative of those encountered for calibration solutions of non-polar organic analytes. Participation in CCQM-K78.b allowed for the benchmarking of capabilities for assigning the mass fraction of non-polar organic compounds (pKow < -2) in solution, at mass fractions above 5 μg/g, in an organic solvent. Additionally, the comparison assessed the capabilities for the quantitative assignment of thermally labile compounds. Participants were provided by the BIPM with ampoules containing methoxychlor and trifluralin in acetonitrile. Each participant reported the mass fraction content of each analyte in μg/g. All participants ensured the metrological traceability of their results through the use of a Primary Reference Material (PRM), which was used to prepare a primary calibrator solution for each analyte using a gravimetric procedure. The twenty participating institutes primarily used analysis procedures based on GC-MS, -IDMS, -MS/MS, -ECD, and -FID, with some participants also using LC-UV for the value assignment. The analysis of methoxychlor and trifluralin in acetonitrile solution presented several challenges, including the thermal stability of the analytes under selected analytical techniques, control of solvent volatility, and considerable variation in some results using MS-based quantification methods. The mass fraction assignments for methoxychlor and trifluralin, consistent with the key comparison reference values (KCRVs), were achieved with associated relative standard uncertainties of (0.38 - 2.9) % for methoxychlor and (0.35 - 2.5) % for trifluralin. 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.083
Threshold uncertainty score0.277

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.035
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0030.001
Scholarly communication0.0060.005
Open science0.0060.004
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0830.037

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 head0.034
GPT teacher head0.387
Teacher spread0.354 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2025
Admission routes1
Has abstractyes

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