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Record W3124026378 · doi:10.15460/hup.67

Union Catalogs at the Crossroad

2004· book· en· W3124026378 on OpenAlexfundno aff
Janifer Gatenby, Rein Van Charldorp, Karen Coyle, Stefan Gradmann, Ole Husby, Annu Jauhiainen, Nadia Caidi, Gabriela Krčmařová, Ilona Trtíková, Martin Lhoták, Bohdana Stoklasová, Pavel Krbec, Lýdia Sedláčková, Alojz Androvič, Błażej Feret, Henryk Hollender, Anna Paluszkiewicz, Andrzej Padziński, Tomasz Wolniewicz, Géza Bakonyi, Klára Koltay, Erik I. Vajda, Janne Andresoo, Riin Olonen, Pierre Malan, Dianne Leong Man, Lettie Erasmus, Amanda Noble, Norma Read

Bibliographic record

Venuenot available
Typebook
Languageen
FieldComputer Science
TopicLibrary Science and Information Systems
Canadian institutionsnot available
FundersUniversity of California, Los AngelesUniversity of TorontoEuropean Bank for Reconstruction and DevelopmentAndrew W. Mellon FoundationUnited States Agency for International Development
KeywordsCatalogingLibrary scienceUnion catalogSoviet unionEuropean unionNational libraryFoundation (evidence)Political scienceWorld Wide WebGeographyComputer scienceBusinessLawInternational trade

Abstract

fetched live from OpenAlex

The Andrew W. Mellon Foundation and the National Library of Estonia organized a Conference on Union Catalogs which took place in Tallinn, in the National Library of Estonia on October 17–19, 2002. The Conference presented and discussed analytical papers dealing with various aspects of designing and implementing union catalogs and shared cataloging systems as revealed through the experiences of Eastern European, Baltic and South African research libraries. Here you can find the texts of the conference papers and the list of contributors and participants.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.103
Threshold uncertainty score0.343

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.009
Science and technology studies0.0060.003
Scholarly communication0.0180.018
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.1030.031

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 head0.012
GPT teacher head0.204
Teacher spread0.192 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2004
Admission routes1
Has abstractyes

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Same topicLibrary Science and Information SystemsFrench-language works237,207