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Record W6945887208 · doi:10.25547/dprw-w642

NDRIO and the Canadian Digital Research Infrastructure Strategy

2024· article· en· W6945887208 on OpenAlexaboutno aff

Bibliographic record

VenueElectronic Textual Cultures Lab · 2024
Typearticle
Languageen
FieldComputer Science
TopicGraph Theory and Algorithms
Canadian institutionsnot available
Fundersnot available
KeywordsDigital governmentGovernment (linguistics)E-GovernmentCritical infrastructureFederal budgetKey (lock)Public policy

Abstract

fetched live from OpenAlex

As reported in “How the 2018 Federal Budget Impacts Research in Canada,” the Government of Canada’s 2018 federal budget included $572.5 million to fund a Digital Research Infrastructure (DRI) Strategy. This DRI Strategy supports data management, research software, advanced research computing (ARC), and other digital research infrastructure in Canada.

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)0.018
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.982
Threshold uncertainty score0.968

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0090.009
Science and technology studies0.0160.005
Scholarly communication0.0240.007
Open science0.0050.009
Research integrity0.0090.006
Insufficient payload (model declined to judge)0.0530.012

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 head0.011
GPT teacher head0.279
Teacher spread0.268 · 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.

Study designNot applicable
DomainMethods
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
Published2024
Admission routes1
Has abstractyes

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