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Record W6929103477 · doi:10.4224/21277164

Évaluation du portefeuille Science des mesures at étalons du CNRC

2015· report· fr· W6929103477 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typereport
Languagefr
FieldDecision Sciences
TopicScientific Measurement and Uncertainty Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsWestern europePublic policyCanadian studies

Abstract

fetched live from OpenAlex

Le présent rapport fait état des résultats de l'évaluation du portefeuille Sciences des mesures et étalons (SME) du Conseil national de recherches du Canada (CNRC) effectuée en 2014‑2015. SME joue au Canada le rôle d'institut national de métrologie (INM), effectue de la recherche et offre des services de métrologie primaires d'intérêt national. À ce titre, SME assure la traçabilité des mesures au Système international d'unités (SI ou système métrique) pour le Canada et assure la participation canadienne aux travaux du Bureau international des poids et mesures (BIPM). Le portefeuille compte troisprogrammes: Métrologie pour l'industrie et la société (MIS), Sciences des mesures pour les technologies émergentes (SMTE) et Soutien scientifique au système national de mesure (SSSNM). Collectivement, les activités menées dans le cadre de ces programmes de SME ont pour objet d'accroître la prospérité sociale et économique du Canada en favorisant l'émergence de produits et de procédés novateurs dans les disciplines où le succès passe obligatoirement par des mesures précises et fiables.

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)0.194
metaresearch head score (Gemma)0.097
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch, Science and technology studies, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.330
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.1940.097
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.006
Science and technology studies0.0040.005
Scholarly communication0.0020.002
Open science0.0030.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0280.007

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 head0.726
GPT teacher head0.474
Teacher spread0.251 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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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Same topicScientific Measurement and Uncertainty EvaluationFrench-language works237,207