Bibliographic record
Abstract
David Krakauer et Kinan Azmeh, compositeurs et clarinettistes de notoriété internationale, se connaissent bien. Ils se sont rencontrés à New York, leur port d’attache. En bientôt quatre décennies, le premier y a façonné son statut de leader du renouveau de la musique klezmer. Le second y affirme son maqam-jazz innovant depuis qu’il a quitté sa Syrie natale en 2001. Fruit savoureux d’une complicité plus qu’artistique, leur toute première création commune est nourrie d’une grande écoute mutuelle et du subtil partage entre les sonorités particulières de leurs répertoires entrelacés. La première mondiale de cette création, commande du festival Haizebegi, triomphait à Anglet, Pays basque, en octobre 2024. À la Saint-Nicolas, elle ravissait le public de Berlin. À l’occasion de cette nouvelle création, les deux artistes se livrent au micro de François Bensignor.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.030 | 0.006 |
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".