Hiding in plain sight: the biomolecular identification of pinniped use in medieval manuscripts
Bibliographic record
Abstract
The survival of medieval manuscripts in their original bindings remains a rare occurrence. Taking advantage of the diversity of bindings in Cistercian libraries such as Clairvaux and its daughter abbeys during the twelfth and thirteenth centuries, this study focuses on the biocodicological analysis of medieval manuscript bindings, with particular emphasis on the use of sealskins. Using innovative methods such as electrostatic zooarchaeology by mass spectrometry (eZooMS) and ancient DNA (aDNA) analysis, this research identifies the animal species and origin of the leather used in these bindings as predominantly pinniped (seal) species. In particular, the collagen-based eZooMS technique facilitated the classification of seven chemises into the pinniped clade, although species identification remained elusive, except in one additional case where a bearded seal ( Erignathus barbatus ) was definitively identified. aDNA analysis was instrumental in verifying the origin of the sealskins, with four samples identified as harbour seals and a single sample as a harp seal and sourced to (contemporary) populations in Scandinavia, Scotland and Iceland or Greenland. This geographical inference supports the notion of a robust medieval trade network that went well beyond local sourcing, linking the Cistercians to wider economic circuits that included fur trade with the Norse. The study, therefore, highlights the use of an unexpected skin (seal) from an unexpected source (the northwestern Atlantic). The widespread use of sealskins in Cistercian libraries such as Clairvaux and its daughter abbeys during the twelfth and thirteenth centuries hints at broader trade networks that brought, for example, walrus ivory from the far north into continental Europe. This integration of the biological sciences into the study of historical manuscripts not only provides a clearer picture of the material culture of medieval Europe, but also illustrates the extensive trade networks that Cistercian monasteries were part of, challenging previous assumptions about local resource use in manuscript production.
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 distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".