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Record W2774128790 · doi:10.1080/0361526x.2017.1391016

Going Out of Business

2017· article· en· W2774128790 on OpenAlexaff
Lorraine Busby

Bibliographic record

VenueThe Serials Librarian · 2017
Typearticle
Languageen
FieldComputer Science
TopicLibrary Collection Development and Digital Resources
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsViewpointsColumn (typography)ManagementPolitical scienceBusinessPublic relationsSociologyEngineeringArtTelecommunicationsVisual artsEconomics

Abstract

fetched live from OpenAlex

The author of The Business of Serials reflects on motivations for the creation of this column and offers some observations and encouragement for others to be a new voice in contributing ideas and viewpoints on the profession of librarianship for today and tomorrow. The column ends with this entry.

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)0.004
metaresearch head score (Gemma)0.015
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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.105
Threshold uncertainty score0.352

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0140.008
Scholarly communication0.0430.020
Open science0.0010.008
Research integrity0.0040.010
Insufficient payload (model declined to judge)0.1050.049

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 head0.037
GPT teacher head0.231
Teacher spread0.194 · 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
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
Published2017
Admission routes1
Has abstractyes

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