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Record W2156534767

INTERNATIONAL RESOURCE COORDINATION: A CISTI PERSPECTIVE

2012· article· en· W2156534767 on OpenAlexaboutno aff
Naomi Krym

Bibliographic record

VenuePurdue e-Pubs (Purdue University System) · 2012
Typearticle
Languageen
FieldDecision Sciences
Topicscientometrics and bibliometrics research
Canadian institutionsnot available
Fundersnot available
KeywordsGovernment (linguistics)Perspective (graphical)Resource (disambiguation)ReputationKey (lock)Information resourceBusinessKnowledge managementInformation sharingShared resourceWorld Wide WebComputer sciencePolitical scienceComputer securityArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

As Canada's scientific and technical "information powerhouse," CISTI has been able to contribute significantly to the development of Canada's knowledge-based economy.CISTI has built on this reputation, sharing its resources and information services internationally.CISTI's scientific and technical information services were developed and supported within Canada, and have been benchmarked for implementation by similar organizations in other countries.This paper will provide appropriate examples of CISTI's role in the Canadian resource-sharing environment, outlining key players, the role of government, and some challenges and opportunities.

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)0.007
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.873

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0130.026
Science and technology studies0.0080.017
Scholarly communication0.0230.011
Open science0.0030.007
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0160.001

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 head0.333
GPT teacher head0.472
Teacher spread0.139 · 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
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
Published2012
Admission routes1
Has abstractyes

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