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Record W4240822590 · doi:10.16995/dm.56

Kiernan, Kevin S. 2015. Electronic Beowulf - Fourth Edition. http://ebeowulf.uky.edu/ebeo4.0/CD/main.html

2015· article· en· W4240822590 on OpenAlexaffvenue
Colleen Copland, Stephen Carrell, Gwendolyn Davidson, Virgil Grandfield, Daniel Paul O’Donnell

Bibliographic record

VenueDigital Medievalist · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicDigital Humanities and Scholarship
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsComputer scienceUsabilityLibrary scienceWorld Wide WebOperating system

Abstract

fetched live from OpenAlex

A review of Kiernan, Kevin S. 2015. Electronic Beowulf, Fourth Edition. (http://ebeowulf.uky.edu/ebeo4.0/CD/main.html). The review discusses issues in usability, editorial approach, and bibliography. It concludes that this digital incunabulum preserves most of the best features of earlier editions while suffering from some bibliographic and technical problems that are instructive for anybody considering a web-based scholarly edition.

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)0.013
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: Other · Consensus signal: none
Teacher disagreement score0.056
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.006
Science and technology studies0.0020.002
Scholarly communication0.0060.010
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0560.030

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 head0.044
GPT teacher head0.247
Teacher spread0.203 · 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

Citations0
Published2015
Admission routes2
Has abstractyes

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