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Record W2616932322 · doi:10.16995/dm.49

The advantages and disadvantages of digital reconstruction and Anglo-Saxon manuscripts

2013· article· en· W2616932322 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueDigital Medievalist · 2013
Typearticle
Languageen
FieldComputer Science
TopicImage Processing and 3D Reconstruction
Canadian institutionsnot available
Fundersnot available
KeywordsPoetryPrayerClass (philosophy)Computer scienceArtHistoryVisual artsLiteraturePhilosophyArtificial intelligenceTheology

Abstract

fetched live from OpenAlex

In editing the Exeter Book poem's "The Descent into Hell," also known as "John the Baptist's Prayer," I attempted to digitally reconstruct the damaged folia that contain the only surviving copy of the Old English poem. In the process of carrying out the digital reconstructive work, many technical, aesthetic and analytical issues were raised. This paper examines many of the techniques used to digitally reconstruct damaged medieval folia using Photoshop, and also assesses the concerns raised during and after the digital reconstructive work was completed. This article also includes an evaluation of many of the benefits as well as the pitfalls of digital reconstruction carried out on ff. 119v-121v of the Exeter Book, and offers practical resolutions that might be considered when digital restorative work is performed on any given damaged medieval MS.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.007
GPT teacher head0.215
Teacher spread0.208 · 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