Traditional beverages of the szlachta court on the Belorussian lands of the Grand Dutchy of Lithuania in the first quarter of the 17th century (under the Mleczko’s manuscript from the Chreptowicz collection in the fonds of the Institute of Manuscript of V. I. Vernadsky National Library of Ukraine)
Bibliographic record
Abstract
The history of traditional beverages of the Belorussian szlachta of the Grand Duchy of Lithuania and the culture of their consumption in the first quarter of the 17th century are covered based on the materials of the manuscript of Orsha standard-bearer Mikolaj Mleczko, which is part of the Chreptowicz collection from the fonds of the Institute of Manuscript of V. I. Vernadsky National Library of Ukraine. Review of historical codicological features of the manuscript is given. Within the historical cultural context a range of old Polish receipts of spirit beverages of the first quarter of the 17th century is analyzed. Based on the texts analysis, it has been established that beer was the most popular beverage in Cholopieniczy estate, which belonged to Mleczko and was located in Orsha lands. Among other issues covered are private contacts of Mikolaj Mleczko, the area of Belorussian beverages distribution, peculiarities and technology of their production, and adoption of new receipts by local consumers - magnates and szlachta of the Grand Duchy of Lithuania. Specifics of the processes of traditional beverages preparation are covered within the history of cuisine culture of Baroque epoch.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".