MétaCan
Menu
Back to cohort
Record W2770497974 · doi:10.1088/1681-7575/aa9a7e

A comparison of future realizations of the kilogram

2017· article· en· W2770497974 on OpenAlexaff
M Stöck, Pauline Barat, Patrick Pinot, Florian Beaudoux, Patrick Espel, François Piquemal, Matthieu Thomas, Djamel Ziane, Patrick J. Abbott, D. Haddad, Zeina J. Kubarych, Jon R. Pratt, Stephan Schlamminger, Kenichi Fujii, Kazuaki Fujita, Naoki Kuramoto, Shigeki Mizushima, L Zhang, Stuart Davidson, R G Green, J. O. Liard, C A Sánchez, Barry Wood, H. Bettin, Michael Borys, I. Busch, M Hämpke, Michael Krumrey, Arnold Nicolaus

Bibliographic record

VenueMetrologia · 2017
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Measurement and Uncertainty Evaluation
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsKilogramPlanck constantRealization (probability)Constant (computer programming)MathematicsValue (mathematics)PhysicsComputer scienceBody weightStatisticsMedicineQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract The definition of the kilogram in the International System of Units (SI) is expected to be revised in 2018. The present definition of the kilogram, the mass of the International Prototype of the Kilogram (IPK), adopted in 1889, would then be replaced by a definition based on a fixed numerical value of the Planck constant. The Consultative Committee for Mass and Related Quantities has requested that, as one of the essential steps before the redefinition, a comparison of kilogram realizations based on future realization methods, Kibble 9 balances and x-ray crystal density (XRCD) experiments, be organized. This comparison was carried out during 2016 in the form of a ‘Pilot Study’. One aim of the study was to determine the uniformity of mass dissemination after the redefinition by comparing mass calibrations based on different future realization experiments. Another aim was to test the continuity of the mass unit across the redefinition by comparing mass calibrations based on Kibble balances and XRCD experiments with those based on the IPK. This paper describes the organization of the comparison and presents its results.

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)0.007
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.023
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.485
GPT teacher head0.540
Teacher spread0.055 · 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 designTheoretical or conceptual
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

Citations31
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueMetrologiaSame topicScientific Measurement and Uncertainty EvaluationFrench-language works237,207