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Record W7036827764

Connecting Readers with Open Access Resources: The CUFTS Free! Open Access Collections Group

2009· other· en· W7036827764 on OpenAlexaboutno aff

Bibliographic record

VenueElpub digital library · 2009
Typeother
Languageen
FieldComputer Science
TopicComputational Physics and Python Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMetadataDirectorySuiteDisseminationFree accessDownloadOpen access publishingDigital library
DOInot available

Abstract

fetched live from OpenAlex

Libraries play an important role in disseminating knowledge. This paper presents an overview of the work of one library group, focused on collection of quality free and open access journals, and illustrates how libraries can be more effective in disseminating knowledge and connecting patrons with needed material by working collaboratively on open access and free collections. Also discussed are the few simple steps that publishers can take to facilitate dissemination of journal content through libraries – following standards such as OpenURL and/or DOI to provide for article-level linking, and providing title lists for download with the key metadata libraries need to include content in library collections, such as title, ISSN, fulltext start date, and journal URL. The CUFTS Free! Open Access Collections Group works collaboratively to connect library patrons with quality open access and free resources, ranging from the international Directory of Open Access Journals to locally developed lists such as Open Access Journals, Open Access Magazines, and Canadian Historic Newspapers. CUFTS is the knowledgebase (journal title lists) of reSearcher, a locally developed open source suite of resources. Through CUFTS, the open access and free journals collections are made available through a link resolving service (GODOT), A to Z journal lists, library catalogues and union databases. A file of MARC records for all of the titles is freely available to download, and downloadable spreadsheets are freely available for local collections as well, from http://www.eln.bc.ca/view.php?id=1129.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmaScholarly communicationOpen science
Domain: not available · Genre: Other
About the Canadian research system: no · About a Canadian topic: no
Not applicablemedium
gptScholarly communication
Domain: not available · Genre: Software
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
models splitAgreement compares identical category sets and study designs across arms.

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)0.040
metaresearch head score (Gemma)0.052
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Open science
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.990
Threshold uncertainty score0.593

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0400.052
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0120.010
Science and technology studies0.0190.007
Scholarly communication0.0350.032
Open science0.0100.038
Research integrity0.0170.010
Insufficient payload (model declined to judge)0.1770.130

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 head0.047
GPT teacher head0.314
Teacher spread0.267 · 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

Labeled directly by 2 models reading the full record.

Scholarly communicationOpen science

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable
Domainnot available
GenreOther · Software

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
Published2009
Admission routes1
Has abstractyes

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