The digital edition of the medieval charters of the Abbey of Saint-Denis: first results and prospects
Bibliographic record
Abstract
In 2006, the École nationale des chartes launched a research project whose main purpose was to edit and publish the almost entirely unedited medieval series of charters of the Abbey of Saint-Denis. Because of the great quantity and dissemination of those charters, the critical edition is a progressive digital work based not on the original documents but on the richest medieval cartulary that has been kept, the Cartulaire blanc (i.e. the “White Cartulary”), which contains 2,600 copies of charters. Olivier Guyotjeannin is the scientific leader of the project, Florence Clavaud is the IT leader. In order to provide quick access to the entire content of the cartulary, the edition integrates images of the manuscript, images and an edition of one of the inventories of the charters (the Inventaire général, i.e. the General Inventory), which was established between 1680 and 1720. This digital corpus now includes about 4,370 images and several XML files (EAD files for the edition of the Inventaire général, TEI files for the ongoing edition of the Cartulaire blanc, METS files to express the relations between the components of the corpus), whose models are explained and discussed. The website has been built by using and adapting open source preexisting tools. It was released in June 2010 (see http://saint-denis.enc.sorbonne.fr), and its content and functionalities are evolving. At this stage of the project, this article includes a prospective assessment of the results obtained.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".