Bibliographic record
Abstract
The Radziwills, an aristocratic family of the Great Duchy of Lithuania, amassed sizable book collections at their estates. Notable is the Nesvizh castle collection, started in the middle of the XVI century by the Great Chancellor of Lithuania, Mikalojus Radvila (Radziwill) the Black.In 1772, after the first division of the Republic of the Two Nations, this collection – one of the state’s largest personal libraries – was removed to the Russian Academy of Sciences in St. Petersburg.The interest in the cultural heritage of the Nesvizh Radziwills in Lithuania was prompted by the iniciative of the cultural institutions of neighbour countries (Poland, Bielorussia and, to a certain degree, Russia) to study the heritage of the Nesvizh Radziwills, dispersed throughout various countries. The last year, the virtual reconstruction of the Radziwills’ collection in Nesvizh was a subject of international scientific conferences and meetings, and of an international pilot project.In Lithuanian libraries, there are several remaining copies with the ex-librises of the Nesvizh Radziwills: three in the Library of the Lithuanian Academy of Sciences, one each in the libraries of Vilnius University, of the Kaunas University of Technology and of the Kazys Varnelis house-museum. The electronic catalogue of the Nesvizh Radziwills’ library, compiled in the Karol Estreicher Institute of Polish Bibliography, includes, among others, a copy from the Library of the Lithuanian Academy of Sciences.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.038 | 0.018 |
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".