Another Fragment of the Old French Romance <i>Meliacin</i>, and Some Observations on Its Place among the Other Earliest Witnesses to the Text
Bibliographic record
Abstract
This article presents a small fragment (only 42 x 138 mm) of a leaf from a manuscript of the Old French poem Meliacin, which once formed part of the stock of the manuscript dealer Erik von Scherling (1907–1956), and came to light in a private collection in 2009. Unknown to the present author, another similarly sized fragment from the same parent-codex, discovered in the binding of a printed book dated 1699, had been published in 2016 by Aurélie Houdebert and Dáibhí Ó Cróinín. The physical materiality of the fragment discussed here agrees with many of Houdebert’s and Ó Cróinín’s conclusions about the dismembered and otherwise lost parent manuscript, and perhaps takes further what we can say about that original codex, its place among the other early witnesses to the text and its intended audience or owners. Furthermore, this scrap of a leaf has more to tell us about the uses and reuses of manuscripts, as distinctive cuts and red ink staining show it to have been reused in early printing as a frisket, most probably in the sixteenth century, before a final reuse to strengthen a later book binding.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".