Bibliographic record
Abstract
This short paper introduces and categorises the mictrotonal writing in my composition Sailing to Byzantium for solo recorder player (1999, published Chipping Norton 2016: Composers Edition). It was delivered at UK Microsoft 1 (Riverside Arts Centre, Walton-on-Thames, 15 October 2005), with live musical excerpts performed by Rachel Barnes. (In the text version of the paper these are rendered as musical illustrations from the manuscript facsimile score). Introductory material covers sources of inspiration for the piece and the use of microtones in it, including the poetry of W B Yeats, the Sequenzas of Luciano Berio, the communicable language of Olivier Messiaen, and Tibetan chant. Three categories of microtonal procedure are then identified: those used structurally using special alternative fingerings; 'bent' pitches used colouristically; and written-out glissandi. Six examples are provided in total, covering all three categories. Pitch-divisions are generally limited to quarter-tones, but eighth-tones are also deployed on occasion. Quarter-tone fingerings are based on Michael Vetter's Blockflütencshcule (Vienna 1983: Universal Edition); eighth-tone fingerings were extrapolated from Vetter's chart via an empirical process of trial-and-error.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".