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Record W2598618555 · doi:10.1088/0026-1394/54/1a/08012

Report of the CCQM-K124: trace elements and chromium speciation in drinking water—part A: trace elements in drinking water, part B: chromium speciation in drinking water

2017· article· en· W2598618555 on OpenAlexaff
Takayoshi Kuroiwa, W H Fung, Yanbei Zhu, Kazumi Inagaki, Della Wai-mei Sin, Hei Shing Chu, David Saxby, Jeffrey Merrick, Ian White, Thiago de Oliveira Araújo, Marcelo Dominguez de Almeida, Jairo Lisboa Rodrigues, Lu Yang, Indu Gedara Pihillagawa, Zoltán Mester, Soraya Sandoval Riquelme, Laura Beatriz Pérez, Ramiro Barriga, Claudia Núñez, J.H. Chao, J Wang, Q Wang, Ni Shi, Hanbing Lu, Ping Song, T Nüykki, T Sara Aho, Guillaume Labarraque, Corinne Oster, Olaf Rienitz, R Jührling, Carsten Pape, Eugenia Lampi, Elias Kakoulides, Rosi Ketrin, E Mardika, Isna Komalasari, Tom Oduor Okumu, J N Kang'iri, Yong Hyeon Yim, Sung Woo Heo, Kwang‐Sik Lee, Jung Kee Suh, Young Ran Lim, Judith Velina Lara Manzano, Christian Uribe, Erica Carrasco, Emma D. Tayag, Admer Rey C. Dablio, Elyson Keith Ponce Encarnacion, R L Damian, L A Konopelko, A. I. Krylov, S Vadim, R.Y.C. Shin, Shanshan Peng, Juan Wu, Xijun Chang, Fransiska Dewi, Marko Horvat, Tea Zuliani, Sutthinun Taebunpakul, Charun Yafa, Nattikarn Kaewkhomdee, Usana Thiengmanee, H Klich, Süleyman Z. Can, Betül Arı, Oktay Cankur, Eduardo Ferreira, Rafael Pérez y Pérez, Stephen E. Long, Brittany L. Kassim, Karen E. Murphy, John L. Molloy, Therese A. Butler

Bibliographic record

VenueMetrologia · 2017
Typearticle
Languageen
FieldChemistry
TopicAnalytical chemistry methods development
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsInductively coupled plasma mass spectrometryChromiumIsotope dilutionChemistryAnalyteInductively coupled plasmaAnalytical Chemistry (journal)Environmental chemistrySpectrophotometryMass spectrometryDistilled waterMetrologyHexavalent chromiumChromatographyRadiochemistryPlasmaMathematicsPhysics

Abstract

fetched live from OpenAlex

CCQM-K124 was organized by the Inorganic Analysis Working Group (IAWG) of CCQM to assess and document the capabilities of the national metrology institutes (NMIs) or the designated institutes (DIs) to measure the mass fractions of trace elements (As, B, Cd, Ca, Cr, Hg and Mo) and hexavalent chromium (Cr(VI)) in drinking water. The National Metrology Institute of Japan (NMIJ) and the Government Laboratory, Hong Kong SAR (GLHK) acted as the coordinating laboratories. This comparison is divided into two parts. Part A was organized by the NMIJ and the trace elements were the analytes, and Part B was organised by the GLHK and Cr(VI) was the analyte. In Part A, results were submitted by 14 NMIs and nine DIs. The participants used different measurement methods, though most of them used direct measurement using inductively coupled plasma-optical emission spectrometry (ICP-OES), inductively coupled plasma-mass spectrometry (ICP-MS), and isotope dilution technique with ICP-MS. The results of As, B, Cd, Ca and Cr show good agreement with the exception of some outliers. Concerning Hg, instability was observed when the sample was stored in the light. And some participants observed instability of Mo. Therefore, it was agreed to abandon the Hg and Mo analysis as this sample was not satisfactory for KC. In Part B, results were submitted by six NMIs and one DI. The methods applied were direct measurement using 1,5-diphenylcarbazide (DPC) derivatisation UV-visible spectrophotometry, standard addition using ion chromatography-UV-visible spectrophotometry or HPLC—inductively coupled plasma-mass spectrometry (ICP-MS) and isotope dilution technique with ion chromatography—ICP-MS. The results of all participants show good agreement. Accounting for relative expanded uncertainty, comparability of measurement results for each of As, B, Cd, Ca, Cr and Cr(VI) was successfully demonstrated by the participating NMIs or DIs. Main text 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 kcdb.bipm.org/ . 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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient 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 score0.496
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.031
GPT teacher head0.287
Teacher spread0.257 · 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".

Quick stats

Citations4
Published2017
Admission routes1
Has abstractyes

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