Изотопный анализ коллагена в изучении пергамена средневековых рукописей: интерпретация первых результатов
Bibliographic record
Abstract
Специфика древнерусского письменного наследия состоит в том, что бóльшая часть средневековых пергаменных кодексов XI–XIV вв. не содержит данных о месте их создания. Это обстоятельство является огромной проблемой отечественной медиевистики. Для ее решения нами была поставлена задача применить изотопный анализ коллагена (метод изотопной масс-спектрометрии) к большому комплексу древнейших пергаменных рукописей, хранящихся в Отделе рукописей Государственного исторического музея. В качестве первого объекта исследования были использованы пробы пергамена четырех новгородских кодексов последней четверти XII – последней четверти XIV в. из собрания Отдела рукописей Государственного исторического музея. Исследования двенадцати проб исторического пергамена были проведены в Институте геохимии и аналитической химии им. В. И. Вернадского (ГЕОХИ) РАН. Первые полученные результаты в области массспектрометрического анализа исторического пергамена нам кажутся вполне убедительными и перспективными для дальнейшего его применения в изучении локализации и элементов технологии изготовления средневековых рукописей. Specific features of Medieval Russia written heritage are stipulated by the fact that most medieval parchment codices do not contain data on the place where they were created. This fact is a true challenge for Russian medieval studies. To address this challenge, our task was to apply stable isotope analysis to a large corpus of the earliest parchment manuscripts kept in the Department of Manuscripts and Early Printed Books of the State Historical Museum. At first, parchment samples of four Novgorod codices dated to the last quarter of the 12th – last quarter of the 14th centuries from the collection of the Department of Manuscripts and Early Printed Books of the State Historical Museum were subjected to this analysis. The analysis of twelve samples of historical parchment was conducted in the Vernadsky Institute of Geochemistry and Analytical Chemistry of the Russian Academy of Sciences. We find the first results of the stable isotope analysis of the parchment quite conclusive and encouraging; hence, this approach can be applied in follow-up studies of the place of production and technological elements of medieval manuscript production.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.050 | 0.017 |
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".