MétaCan
Menu
Back to cohort
Record W6930691097 · doi:10.5281/zenodo.14982727

Investing in an efficient and transparent research ecosystem in Canada - Investir dans un écosystème de recherche efficace et transparent au Canada

2025· report· en· W6930691097 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typereport
Languageen
FieldEngineering
TopicAdvanced Electrical Measurement Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)Control (management)Work (physics)Scope (computer science)Equity (law)

Abstract

fetched live from OpenAlex

<p>In 2021, the Canadian Research Knowledge Network (CRKN) in partnership with the Digital Research Alliance of Canada consulted with <a href="https://www.morebrains.coop/">MoreBrains Cooperative</a>, international experts in PIDs and PID Strategy development, to assess the state of PIDs in Canada and laying the foundation for a national strategy. This 2024 report, undertaken on behalf of and reviewed by the <a href="https://www.crkn-rcdr.ca/en/persistent-identifier-pid-governance" target="_blank" rel="noopener noreferrer">Canadian Persistent Identifier Advisory Committee (CPIDAC)</a>, synthesizes findings from three phases of research, consultation, and analysis. It refines the vision, priorities, and key PIDs while providing actionable recommendations based on extensive stakeholder engagement. MoreBrains highlights governance, technical capacity, leadership, and community engagement as critical to advancing PID adoption and building a more efficient, trustworthy, and interoperable research ecosystem.</p> <p>***************************</p> <p>En 2021, le Réseau canadien de documentation pour la recherche (RCDR) en partenariat avec l’Alliance de recherche numérique du Canada a fait appel à <a href="https://www.morebrains.coop/">MoreBrains Cooperative</a>, des spécialistes internationaux en matière de PID et d’élaboration de stratégies sur les PID, afin d’évaluer la situation des PID au Canada et établir les bases d’une stratégie nationale. Ce rapport de 2024, réalisé au nom du <a href="https://www.crkn-rcdr.ca/fr/gouvernance-identifiants-perennes-pid">Comité consultatif canadien sur les identifiants pérennes (CCCPID)</a> et examiné par celui-ci, synthétise les résultats de trois phases de recherche, de consultation et d’analyse. Le rapport peaufine la vision, les priorités et les principaux PID tout en proposant des recommandations concrètes basées sur une large mobilisation des parties prenantes. MoreBrains souligne que la gouvernance, la capacité technique, le leadership et l’engagement de la communauté sont essentiels pour favoriser l’adoption des PID et bâtir un écosystème de recherche plus efficace, fiable, et interopérable.</p>

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)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.790
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.227
GPT teacher head0.339
Teacher spread0.112 · 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.

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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueZenodo (CERN European Organization for Nuclear Research)Same topicAdvanced Electrical Measurement TechniquesFrench-language works237,207