Bibliographic record
Abstract
The power to make your own tools completely changes the creative process. You can envision a unique solution to a problem and, if it isn’t available, create it yourself. In my sound work outside of theatre, I developed a software instrument called Kenaxis that lets me quickly grab hold of sounds, manipulate them, mangle them, change to a different set of sounds, grab live samples and, if the setup allows, do it all in surround sound. This software is perfect for experimental theatre, places where improvisation and an emphasis on gestures is important, and for working in alternative spaces with surround sound. It allows the environment to be more playful and removes the need to set sound parameters rigidly ahead of time. Compositionally, the software is set up to provide an environment where any number of things can happen: a space where various processes can be applied to the sound — deliberate or random — allowing the software to create a different sound design for each performance. However, while Kenaxis was the perfect tool for experimenting with sound, it is not optimized for a cue-to-cue approach to sound design.
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 | 0.000 | 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".