Bibliographic record
Abstract
Le Moyen Âge nous a légué un certain nombre de traductions bibliques. Pour le philologue moderne se pose constamment la question de la source à partir de laquelle elles ont pu être effectuées. Si le manuscrit que le translateur avait sous les yeux n’est jamais identifiable, il reste à déterminer le type de texte qu’il a pu utiliser. On sait en effet que la Vulgate n’était pas toujours la seule référence et qu’on la complétait assez facilementà l’aide d’autres histoires bibliques : les Antiquités judaïques de Flavius Josèphe, l’Historia scholastica de Petrus Comestor ou l’Aurora de Petrus Riga. Par-delà se pose cependant une autre question : le translateur effectuait-il toujours une traduction à nouveaux frais et ne lui arrivait-il pas de réutiliser, en l’adaptant quelque peu, un travail effectuépar un autre ? Paul Meyer avait montré, en son temps, que la Genèse livrée par le MS fr.6447 de la Bibliothèque nationale de France était un dérimage partiel de la Bible d’ Hermann de Valenciennes et d’un autre poème non encore identifié.
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 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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.022 | 0.006 |
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".