Sygaldry : logiciel réutilisable pour la fabrication d’instruments de musique numériques
Bibliographic record
Abstract
Digital musical instruments are a family of instruments whose excited medium is digital audio signals. Their design and development has been the subject of research for over 30 years, and certain tools, techniques, and materials have begun to emerge as standard components for making digital musical instruments. In order to support the long-term maintenance and replication of these instruments, so as to enable long-term research and creative practice and foster the development of our collective digital musical instrument design savvy, we propose to develop a library of reusable digital musical instrument components. Existing libraries are unable to cover the wide range of components, hardware platforms, and software environments used in the making of digital musical instruments, due to issues of glue code, limited software interface, and runtime performance. Leveraging modern C++ design patterns based on compile-time reflection and metaprogramming, we address these issues. Our library, Sygaldry, provides immediate benefit to the replication, porting, and validation of digital musical instruments.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".