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Record W7105802652 · doi:10.48336/41

Composing entries for the cartulary of Theuley in twelfth-century France

2025· other· en· W7105802652 on OpenAlexfundno aff

Bibliographic record

VenueOpen MIND · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersVlaamse regeringMemorial University of NewfoundlandUniversity of Cambridge
KeywordsCopyingMicroformFoundation (evidence)Composition (language)Period (music)

Abstract

fetched live from OpenAlex

The foundation of the Cistercian abbey of Theuley, located in Burgundy, France, is described in its cartulary which was composed in the late twelfth or early thirteenth century. Despite an especially rich archive, Theuley has been little studied as a result of its distance from the chief cultural centres of Dijon, Langres and Besançon as well as the presence of a large number of its documents being in private hands. This thesis examines the first few entries of the cartulary by means of a careful historical analysis of the Latin text, aided by a comparison to other sources, both in manuscript and printed forms. All the studied texts in the cartulary have been found to use extracts from other formal documents, but with significant additions and deletions. In a few cases, the extracts themselves appear to be used in earlier donations with completely different donors and different witnesses. The author of the cartulary both deleted dates from the extracts and added a date to the foundation document. The composition of this cartulary was clearly not a simple copying of existing documents. This study thus contributes to the developing understanding of the varied nature of cartularies in the medieval world.

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)0.001
metaresearch head score (Gemma)0.002
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: none
Teacher disagreement score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0050.003
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0110.001

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 head0.022
GPT teacher head0.316
Teacher spread0.295 · 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
Published2025
Admission routes1
Has abstractyes

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