Bibliographic record
Abstract
В статье содержится характеристика содержания текста «Моих воспоминаний об Иване Вышнеградском» Брюса Матера (р. 1939). Подчеркивается, что появление этих воспоминаний на русском языке — крупное событие в истории возвращения наследия Ивана Вышнеградского на родину. Одновременно автор статьи анализирует творческий путь известного канадского музыканта в свете его отношений с Вышнеградским, который оказал огромное влияние на становление его личности и стиля. Матер — едва ли не единственный ныне живущий ученик и последователь Вышнеградского, заложивший основу школы микротоновой музыки в Канаде. Содержащаяся в статье информация о творческих связях Матера и Вышнеградского, а также подробности биографии самого Матера представляются в отечественном музыкознании впервые. The article contains a description of the content of the text of “My memories of Ivan Wyschnegradsky” by Bruce Mather (b. 1939). It is emphasized that the appearance of these memories in Russian is a major event in the history of the return of Wyschnegradsky’s legacy to his homeland. At the same time, the author analyzes the creative path of the famous Canadian musician in the light of his relationship with Ivan Wyschnegradsky, who had a huge impact on the formation of his personality and style. Mather is almost the only living student and follower of Wyschnegradsky, who laid the Foundation for the school of microtonal music in Canada. The information contained in the article about the creative ties between the Mather and Wyschnegradsky, as well as the details of the Mather’s biography, are presented in the Russian press for the first time.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".