Bibliographic record
Abstract
The TORONTO MEDIEVAL LATIN TEXTS series is published by the Pontifical Institute of Mediaeval Studies for the Centre for Medieval Studies at the University of Toronto.The series produces affordable editions, generally based on a single carefully chosen manuscript, suitable for use in university-level courses in medieval Latin.In approving projects, the editorial board bears in mind the pedagogical utility of the texts proposed.Since the appearance in 1972 of its first volume, the series has produced over thirty such editions, volumes 1 to 30 edited by A.G. Rigg, and volumes 31 through 35 by David Townsend, with Anna Burko and Philippa Matheson, respectively, as editorial assistants.With volume 36 the series comes under the editorship of Greti Dinkova-Bruun and Alexander Andrée.We are deeply indebted to George and David for their sustained and tireless work as general editors and for setting a daunting standard to emulate.While classroom utility and affordability remain hallmarks of the enterprise, the series also aims to further original research by publishing previously unedited texts from reliable single-manuscript versions of particular textual, historical, and codicological interest and importance, in recognition that the scribal makers of such versions were important participants in the ongoing development of the text.The manuscript is emended only to restore sense, not to reconstruct an original authorial version or an archetype; the minimal critical apparatus omits variants irrelevant to the integrity of the selected manuscript.Manuscript orthography and syntax are carefully preserved.The scope and
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.457 | 0.220 |
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".