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Record W4283396231 · doi:10.1088/1681-7575/ac7bc1

NRC measurement set-up and preparatory work for CCT-K7.2021 key comparison of triple-point-of-water cells

2022· article· en· W4283396231 on OpenAlexaff
Andrea Peruzzi, Sergey Dedyulin

Bibliographic record

VenueMetrologia · 2022
Typearticle
Languageen
FieldEngineering
TopicCalibration and Measurement Techniques
Canadian institutionsNational Research Council CanadaMétis National Council
Fundersnot available
KeywordsTriple pointWork (physics)Significant differenceResearch councilComputer scienceAnalytical Chemistry (journal)MathematicsChemistryStatisticsPhysicsEnvironmental chemistryThermodynamics

Abstract

fetched live from OpenAlex

Abstract This paper describes the NRC measurement set-up and the preparatory work for the CCT-K7.2021 key comparison (KC) of triple-point-of-water (TPW) cells. The preparatory work at NRC (charged with piloting the KC) included a comprehensive testing of the measurement set-up, the definition of the new NRC national standard for the TPW temperature, and the evaluation of the uncertainty budgets relevant for this KC. The new NRC TPW national standard is composed of an ensemble of ten fused silica TPW cells, characterized in both their isotopic composition and impurity content. Three uncertainty budgets were evaluated, corresponding to three different cases involved in the measurements at the pilot laboratory: (a) the temperature difference between two TPW cells, which amounted to 26 μK (k = 2), (b) the temperature difference between a TPW cell and NRC national reference, which amounted to 35 μK (k = 2) and (c) the temperature difference between a comparison participant’s transfer cell and the comparison reference, composed of the average of two NRC national reference cells, which amounted to 19 μK (k = 2).

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)0.008
metaresearch head score (Gemma)0.008
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0020.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.004

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 head0.053
GPT teacher head0.262
Teacher spread0.209 · 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".

Quick stats

Citations5
Published2022
Admission routes1
Has abstractyes

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