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Record W4414540407 · doi:10.1088/0026-1394/62/1a/07024

Final report on the CCM key comparison of density measurements of a silicon sphere (1 kg) by hydrostatic weighing (CCM.D-K1.2023)

2025· article· en· W4414540407 on OpenAlexaff
Daniela Eppers, Luis Omar Becerra, Andrea Malengo, K. Marti, R G Green, Nathan F. Murnaghan, Xiang Liu, Naoki Kuramoto, Atsushi Waseda, Kanako Nishihashi, Mohammed Mohammed, Alaaeldin A. Eltawil, K Fen, Beste Korutlu, Özlem Pehlivan, R A Alyousefi, Khaled S AlEnizi

Bibliographic record

VenueMetrologia · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Measurement and Uncertainty Evaluation
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMetrologyMutual recognitionHydrostatic equilibriumKey (lock)Equivalence (formal languages)Measurement uncertainty

Abstract

fetched live from OpenAlex

Main text This report presents the results of the key comparison CCM.D-K1.2023 of solid density measurements by hydrostatic weighing, which was carried out through May 2022 to June 2024. As transfer standard act a 1 kg sphere made of natural silicon, which is compared directly or indirectly to primary density standards calibrated by mass and dimensional measurements. Ten laboratories participated in this key comparison of five regional metrology organizations (RMO): three of European association metrology institutes (EURAMET), three of Asia pacific metrology programme (APMP), two of inter-American metrology system (SIM), one of intra-Africa metrology system (AFRIMET) and one of Gulf association for metrology (GULFMET). This CIPM key comparison, was coordinated by the Physikalisch-Technische Bundesanstalt (PTB, DE) as the pilot laboratory, and Centro Nacional de Metrología (CENAM) and Istituto Nazionale di Ricerca Metrologica (INRIM) as co-pilot laboratories. The Key Comparison Reference Values (KCRVs) have been obtained for the volume and density values related to the transfer standard by the results of participants, whereby the method of least squares χ2 is estimated. The KCRVs and the corresponding uncertainties were calculated by the weighted mean in case of consistent results. Only two laboratories differed and were excluded from the analysis (En-value greater than 1). For each participant, the degree of equivalence (DoE) was determined with respect to the corresponding KCRV and between the other laboratories. 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 CCM, 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)0.020
metaresearch head score (Gemma)0.019
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0200.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.354
GPT teacher head0.438
Teacher spread0.084 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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