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Record W2797556907 · doi:10.1088/1361-6501/aabc9e

The Planck-Balance—using a fixed value of the Planck constant to calibrate E1/E2-weights

2018· article· en· W2797556907 on OpenAlexfundno aff
Christian Rothleitner, Jan Schleichert, Norbert Rogge, Ludwig Günther, Suren Vasilyan, F. Hilbrunner, Dorothea Knopf, Thomas Fröhlich, Frank Härtig

Bibliographic record

VenueMeasurement Science and Technology · 2018
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Measurement and Uncertainty Evaluation
Canadian institutionsnot available
FundersNational Research Council CanadaBundesministerium für Bildung und Forschung
KeywordsPlanck constantPlanckPhysicsCalibrationPlanck massChristian ministryConstant (computer programming)Standard uncertaintyPlanck lengthMeasurement uncertaintyComputer sciencePlanck scaleQuantum mechanics

Abstract

fetched live from OpenAlex

Abstract A balance is proposed, which allows the calibration of weights in a continuous range from 1 mg to 1 kg using a fixed value of the Planck constant, h . This so-called Planck-Balance (PB) uses the physical approach of Kibble balances that allow the Planck constant to be derived from the mass. Using the PB no calibrated mass standards are required during weighing processes any longer, because all measurements are traceable via the electrical quantities to the Planck constant, and to the meter and the second. This allows a new approach of balance types after the expected redefinition of the SI-units by the end of 2018. In contrast to many scientific oriented developments, the PB is focused on robust and daily use. Therefore, two balances will be developed, PB2 and PB1, which will allow relative measurement uncertainties comparable to the accuracies of class E2 and E1 weights, respectively, as specified in OIML R 111-1. The balances will be developed in a cooperation of the Physikalisch-Technische Bundesanstalt (PTB) and the Technische Universität Ilmenau in a project funded by the German Federal Ministry of Education and Research.

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)0.004
metaresearch head score (Gemma)0.007
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: Methods · Consensus signal: Methods
Teacher disagreement score0.009
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0030.005
Open science0.0020.003
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0090.006

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 head0.183
GPT teacher head0.369
Teacher spread0.186 · 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
GenreMethods

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

Citations47
Published2018
Admission routes1
Has abstractyes

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