Bibliographic record
Abstract
The article for the first time in Ukrainian historiography, museology and monumentology considers works of European fine art, where there is an image of a wind wooden musical instrument bassoon. Works of painting, graphics, works of monumental art (sculpture) are analyzed. This is a characteristic of the collections of bassoons in museums in Western Europe, the USA and Canada. Publications stored in the funds of the Vernadsky National Library of Ukraine, Yaroslav Mudryi National Library Of Ukraine, the National Historical Library of Ukraine, the National Scientific and Research Restoration Center of Ukraine were used. The expositions of the Bohdan and Varvara Khanenko National Museum of Arts (Kyiv), the Museum of Theatrical, Musical and Film Art of Ukraine (Kyiv), the State Yagotynsky Historical Museum (Yagotyn, Kyiv Region), as well as Internet resources of collections of wind instruments of a number of museums in Europe, the USA and Canada are analyzed. Materials from the personal archive and musical collection of the bassoonist, teacher in the class of wind musical instruments, soloist of orchestra V. Kepin (Kyiv) were involved. Based on the analysis, it was concluded that the Flemish artist Dеnis van Alsloot can be considered one of the first in European painting, which brought to our time the composition of wind musical instruments characteristic of the musical culture of Western Europe of the XVII century. In Ukraine, one of the oldest copies of the bassoon (1730s) is stored in the Museum of Theatrical, Musical and Film Art of Ukraine (Kyiv).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.009 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".