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Record W4285164430 · doi:10.1088/0026-1394/59/1a/02002

Final report on the CCPR Key Comparison CCPR-K3.2014 Luminous Intensity

2022· article· en· W4285164430 on OpenAlexaffabout
Arnold A. Gaertner, Éric Côté, Gaël Obein, Peter Blattner, Reto Schafer, Hui Liu, C. A. Miller, Yuqin Zong, E G Atkinson, Erik Thorvaldson, K. Kinoshita, Rheinhardt Sieberhagen, Irma Rabe, Teresa Goodman, Barry Scott, Armin Sperling, Detlef Lindner, Boris Khlevnoy, Evgeniy Ivashin

Bibliographic record

VenueMetrologia · 2022
Typearticle
Languageen
FieldEngineering
TopicCalibration and Measurement Techniques
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMutual recognitionNISTMetrologyPhotometry (optics)Environmental scienceMathematicsLibrary scienceComputer scienceStatistics

Abstract

fetched live from OpenAlex

Main text The metrological equivalence of national measurement standards in the field of photometry and radiometry is determined by a set of key comparisons chosen and organised by the Consultative Committee of Photometry and Radiometry (CCPR) of the Comité international des poids et mesures (CIPM), working closely with the Regional Metrology Organisations (RMOs). In September 2009 the CCPR decided that a second round of the key comparison K3 Luminous Intensity be commenced. The National Research Council of Canada (NRC) was chosen to pilot this comparison. A total of 12 participants were selected from the three RMO group members: EURAMET&COOMET (6: IO-CSIC, LNE-CNAM, METAS, NPL, PTB, VNIIOFI), APMP&AFRIMETS (4: NMISA, NIM, NMIA, NMIJ), and SIM (2: NIST, NRC). The comparison was organised as a star comparison (NMI-Pilot-NMI) using incandescent standard lamps supplied by each NMI (National Metrology Institute) as the travelling comparison artifact. This report describes the comparison organisation (Section 2), the measurement methods and uncertainties achieved at all the participants and at the pilot (Sections 3 and 4), and the method for analysis and the results of the comparison according to this method (Section 4). It includes a comparison of the results of this comparison with the 1999 first round key comparison (Section 5). Section 6 presents a summary of the comparison. 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 https://www.bipm.org/kcdb/ . The final report has been peer-reviewed and approved for publication by the CCPR, 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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score0.628

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.057
GPT teacher head0.253
Teacher spread0.196 · 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 designNot applicable
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

Citations2
Published2022
Admission routes2
Has abstractyes

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