Control parameters for musical instruments: a foundation for new mappings of gesture to sound
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In this paper we describe a new way of thinking about musical tones, specifically in the context of how features of a sound might be controlled by computer musicians, and how those features might be most appropriately mapped onto musical controllers. Our approach is the consequence of one bias that we should reveal at the outset: we believe that electronically controlled (and this includes computer-controlled)musical instruments need to be emancipated from the keyboard metaphor; although piano-like keyboards are convenient and familiar, they limit the musician's expressiveness (Mathews 1991, Vertegaal and Eaglestone 1996, Paradiso 1997, Levitin and Adams 1998). This is especially true in the domain of computer music,in which timbres can be created that go far beyond the physical constraints of traditional acoustic instruments.
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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 it