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Record W2242451433 · doi:10.1088/0026-1394/52/1a/01014

SIM regional comparison of ac-dc current transfer difference SIM.EM-K12

2015· article· en· W2242451433 on OpenAlexaboutno aff
Lucas Di Lillo

Bibliographic record

VenueMetrologia · 2015
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadioactive Decay and Measurement Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCurrent (fluid)Transfer (computing)PhysicsEnvironmental scienceMaterials scienceComputer scienceThermodynamics

Abstract

fetched live from OpenAlex

The ac-dc current transfer difference identified as SIM.EM.K-12 began in July 2010 and was completed in September 2012. Six NMIs in the SIM region and one NMI in the AFRIMET region took part: NRC (Canada), NIST (United States of America), CENAM (Mexico), INTI (Argentina), UTE (Uruguay), INMETRO (Brazil) and NIS (Egypt). The comparisons were proposed to assess the measurement capabilities in ac-dc current transfer difference of the participants NMIs. The ac-dc current transfer differences of the travelling standard had been measured at 10 mA and 5 A at 10 Hz, 55 Hz, 1 kHz, 10 kHz, 20 kHz, 50 kHz and 100 kHz. The test points were selected to link the results with the equivalent CCEM Key Comparisons (CCEM-K12), through three NMIs participating in both SIM and CCEM key comparisons (INTI, NRC and NIST). The report shows the degree of equivalence in the SIM region and also the degree of equivalence with the corresponding CCEM reference value. The results of all participants support the values and uncertainties of the applicable CMC entries for ac-dc current transfer difference in the Key Comparison Database held at the BIPM. 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 CCEM, 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.543

Codex and Gemma teacher scores by category

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

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 head0.133
GPT teacher head0.348
Teacher spread0.215 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2015
Admission routes1
Has abstractyes

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