Омелян Антонович – громадський діяч, дослідник, меценат (до 100-річчя від дня народження) (Public Figure, Researcher, and Philanthropist Omelan Antonovych (on the Occasion of His 100th Birthday Anniversary))
Bibliographic record
Abstract
У статті, присвяченій пам’яті відомого мецената, громадського діяча у США та Україні, висвітлено деякі маловідомі сторінки його життя, громадської і дослідницької діяльності на основі документів особистого архіву Омеляна і Тетяни Антоновичів у відділі рукописів Львівської національної наукової бібліотеки ім. В. Стефаника (The article is dedicated to the memory of the well-known Antonovych Foundation creator, as well as public activist in the US and Ukraine Omelan Antonovych. The author states that Antonovych personal documents reveal some unknown facts about his public and research activity which was not described in his two books of Memoirs (1999, 2003). Omelan Antonovych was an active member of the Foreign Representation of the Ukrainian Supreme Liberation Council, the Prolog Research and Publishing Corporation, the Ukrainian Association of Washington State, DC, etc. He found and selected German archival official documents about OUN that were published in the 21st volume of Litopys UPA (Toronto, 1991). His life is an example of selfless service to Ukrainian people and Ukraine. The personal archive of Dr. Omelan Antonovych and his wife prof. Tatiana Terlecka are kept in Vasyl Stefanyk Lviv National Scientific Library of Ukraine)
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.008 |
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".