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Record W4236348901 · doi:10.1088/0026-1394/54/1a/07019

Regional comparison of absolute gravimeters SIM.M.G-K1 key comparison

2017· article· en· W4236348901 on OpenAlexaff
D B Newell, D van Westrum, Olivier Francis, J Kanney, J Liard, A E Ramirez, B Lucero, B Ellis, Filippo Greco, A Pistorio, R Reudink, D Iacovone, F Baccaro, J Silliker, R D Wheeler, Reinhard Falk, A Ruelke

Bibliographic record

VenueMetrologia · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeophysics and Gravity Measurements
Canadian institutionsNatural Resources CanadaNational Research Council Canada
Fundersnot available
KeywordsGravimeterMutual recognitionGeodesyMathematicsPhysicsGeographyGeophysics

Abstract

fetched live from OpenAlex

Twelve absolute gravimeters were compared during the regional Key Comparison SIM.M.G-K1 of absolute gravimeters. The four gravimeters were from different NMIs and DIs. The comparison was linked to the CCM.G-K2 through EURAMET.M.G-K2 via the DI gravimeter FG5X-216. Overall, the results and uncertainties indicate an excellent agreement among the gravimeters, with a standard deviation of the gravimeters' DoEs better than 1.3 μGal. In the case of the official solution, all the gravimeters are in equivalence well within the declared uncertainties. 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 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 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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.004
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.014

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 head0.100
GPT teacher head0.307
Teacher spread0.207 · 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 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

Citations8
Published2017
Admission routes1
Has abstractyes

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