Bibliographic record
Abstract
Воспоминания канадского композитора Брюса Матера представляют собой уникальное свидетельство о последних годах жизни и творчества выдающегося русского композитора Ивана Вышнеградского (1893–1979), одного из основоположников европейской микротоновой музыки. Под пером Матера личность Вышнеградского предстает во всей своей полноте: как композитора, теоретика, педагога, подвижника. Особую ценность тексту воспоминаний придают письма Вышнеградского, в которых запечатлен стиль речи и мышления композитора. Одно[1]временно Матер короткими, но точными штрихами передает дух эпохи и нюансы художественной жизни Франции и Канады 1970-х годов. На русском языке «Воспоминания» Брюса Матера публикуются впервые. “My memories of Ivan Wyschnegradsky” by Canadian composer Bruce Mather is one of the unique testimonies about the last years of life and work (1974–1978) of the outstanding Russian composer, one of the founders of European microtonal music. Under the pen of Mather, Wyschnegradsky’s personality appears in its entirety: as a composer, theorist, teacher, and ascetic. Wyschnegradsky’s letters, which capture the composer’s style of speech and thinking, add special value to the text of his memoirs. At the same time, Mather conveys the spirit of the time and the nuances of the artistic life of France and Canada in the 1970s in short but precise strokes. In Russian, “Memoirs” by Bruce Mather is published for the first time.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".