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Record W6891684439 · doi:10.4224/21277165

Evaluation of NRC Measurement Science and Standards

2015· report· en· W6891684439 on OpenAlexfundaboutno aff

Bibliographic record

VenueNational Research Council Canada (Government of Canada) · 2015
Typereport
Languageen
Field
Topic
Canadian institutionsnot available
FundersNational Physical LaboratoryNatural Resources CanadaGovernment of CanadaCanadian Nuclear Safety CommissionNational Institute of Standards and TechnologyNational Research Council CanadaIndustry CanadaHealth CanadaMinistère de la Défense Nationale
KeywordsMetrologyTraceabilityProsperityProduct (mathematics)PortfolioProcess (computing)

Abstract

fetched live from OpenAlex

This report presents the results of the 2014‑15 evaluation of the National Research Council (NRC) Measurement Science and Standards (MSS) Portfolio. MSS is Canada's national metrology institute (NMI), conducting research and providing primary metrology services in the national interest. In this role, MSS provides traceability to the International System of Units (the SI, or metric system) for Canada and supports Canada's participation in the Bureau international des poids et mesures (BIPM). The Portfolio hosts three programs: Metrology for Industry and Society (MIS), Measurement Science for Emerging Technologies (MSET), and Scientific Support for the National Measurement System (SSNMS). Together, MSS activities aim to improve social and economic prosperity by enabling both product and process innovation in areas where precise and reliable measurements are critical to success.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaMetaresearch
Domain: Evaluation · Genre: Empirical
About the Canadian research system: yes · About a Canadian topic: yes
Not applicablehigh
gptMetaresearch
Domain: Evaluation · Genre: Other
About the Canadian research system: yes · About a Canadian topic: yes
Not applicablelow
models agreeAgreement compares identical category sets and study designs across arms.

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)0.946
metaresearch head score (Gemma)0.973
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesMetaresearch
DomainCandidate signal: Evaluation · Consensus signal: Evaluation
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.999
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.9460.973
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.488
GPT teacher head0.416
Teacher spread0.073 · 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

Labeled directly by 2 models reading the full record.

Study designNot applicable
DomainEvaluation
GenreEmpirical · Other

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 routes2
Has abstractyes

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Same venueNational Research Council Canada (Government of Canada)CategoryMetaresearchFrench-language works237,207