EMS: Electroacoustic Music Studies Network – Montréal 2005 Musical objects and digital domains
Bibliographic record
Abstract
This paper deals with the production, representation and mutation of musical objects within digital media spaces. The influence of computer science on artistic practices and the modes of production of digital objects are treated. Besides, the ideas of Pierre Schaeffer, Giorgy Ligeti, Iannis Xenakis and Gerard Grisey relating to a frame of extra-musical reference are briefly mentioned, since each author, in the construction of the musical object, revealed a different approach. The decoding of structures from one sensorial channel to another is the next issue, devoted to Moles ’ research on multiple messages, functional analogies and the creation of artificial channels. An overview of how artistic-technological experimentation over the last twenty years has dealt with the conversion of digital objects within multimedial, interactive events follows. To conclude, there is a comment on the views of composers and digital communication scholars regarding the “objective status ” of digital objects within the cyberspace.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.298 | 0.054 |
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".