Bibliographic record
Abstract
Details: \nSilk to Steel is a multi-channel (5.1 and 7.1) composition. It was a Finalist at CIMESP 2005, Brazil, and received an Honourable \nMention at the Bourges International Electroacoustic Music Competition 2005. There have been 17 further performances, \nincluding VI CIMESP 2005, Goethe-Institut, São Paulo; Elektrophonie, Dijon, France; Sounds Electric’05, Aula Maxima, \nMaynooth, Ireland; Fylkingen Institute, Stockholm; Concordia University, Montreal; VI International Festival of Electroacoustic \nMusic, Santiago, Chile; Logos Foundation, Gent, Belgium; Seoul International Computer Music Festival, Jayu Theatre, Seoul, \nKorea. \n \n \nPortfolio: \n‘The influence of Futurist painting techniques in my music’, in the proceedings of the Digital Music Research Network \nConference, Leeds Metropolitan University, 7–8 July 2007. \n \n \nContext: \nSilk to Steel is a 50th birthday tribute to the composer Christopher Fox and utilises selected passages from Fox’s piano work \nPrime Site as its source material. The structure of Silk to Steel is also derived from Fox’s work. The original seven movements \nof Prime Site are concentrated into seven interlinking sections, each like Fox’s, focusing on rhythm, space, harmony, gestural \ncounterpoint and density. Rather than create a series of standard variations, the work continues the composer’s research into \nthe application of Futurist painting techniques in electronic music by refracting the source materials through the techniques of \ndivisionism and dynamism. The application of divisionism to sound materials also provides an original means of structuring \nspatial elements as opposed to algorithmic or traditional sound diffusion techniques. In Silk to Steel 13 spatial planes for sonic \nmaterial were created that can interpenetrate one another, with the timbre, rhythm or trajectory of the sound changing as they \ndo so. These processes are further explained in the portfolio article.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.305 | 0.001 |
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; both teacher heads agree on what is shown here.
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".