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Record W2596855125 · doi:10.1080/0361526x.2017.1292751

The Canadian Linked Data Initiative: Charting a Path to a Linked Data Future

2017· article· en· W2596855125 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Serials Librarian · 2017
Typearticle
Languageen
FieldComputer Science
TopicLibrary Science and Information Systems
Canadian institutionsnot available
Fundersnot available
KeywordsMetadataLibrary scienceWork (physics)Linked dataDigital libraryAdaptation (eye)Path (computing)Political scienceWorld Wide WebComputer scienceEngineering

Abstract

fetched live from OpenAlex

This article is a preliminary report on the work of the Canadian Linked Data Initiative (CLDI), a collaboration between five of Canada’s largest research libraries, Library and Archives Canada, Bibliothèque et Archives nationales du Québec, and Canadiana.org. Although still in its nascent stage, participating institutions are working together to advance the technical services divisions of our libraries in the area of linked data. Project working groups are making progress in five main areas: grant funding, digital collections, education and training, legacy metadata enhancement, and in the evaluation and adaptation of Bibliographic Framework Transition Initiative tools. By working across geographic and institutional boundaries, the CLDI aims to chart a path to a new age of technical services, one based on the foundation of Linked Open Data.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Open science
Consensus categoriesScholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.948
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0050.000
Scholarly communication0.0120.027
Open science0.0290.007
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.149
GPT teacher head0.308
Teacher spread0.159 · 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