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Record W2067425171 · doi:10.1080/01462679.2012.685420

Three Libraries, Three Weeding Projects: Collaborative Weeding Projects Within a Shared Print Repository

2012· article· en· W2067425171 on OpenAlexaff
Scott Gillies, Carol Stephenson

Bibliographic record

VenueCollection Management · 2012
Typearticle
Languageen
FieldComputer Science
TopicLibrary Collection Development and Digital Resources
Canadian institutionsWilfrid Laurier UniversityUniversity of Guelph
Fundersnot available
KeywordsScope (computer science)Library scienceWorld Wide WebPolitical scienceComputer scienceBusiness

Abstract

fetched live from OpenAlex

The Tri-University Group of Libraries has operated a joint print repository (the Annex) since 1996. As of March 2011, the facility is at 94% capacity. Following a shutdown and comprehensive review in 2006, the three institutions developed a Preservation of Last Print Copy Agreement. This agreement spurred the three partner institutions to undertake three specific weeding projects (monographs deduplication, weeding of science, technology, and medicine journals, and a JSTOR journals last copy project) to prolong the life of the repository. This article outlines the scope, methodologies, successes, and challenges involved with these collaborative weeding projects.

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)0.050
metaresearch head score (Gemma)0.054
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.984
Threshold uncertainty score0.264

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0500.054
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.008
Science and technology studies0.0150.006
Scholarly communication0.0160.011
Open science0.0040.023
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0090.003

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 head0.034
GPT teacher head0.221
Teacher spread0.187 · 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

Citations16
Published2012
Admission routes1
Has abstractyes

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