Bibliographic record
Abstract
The thesis for the Master of Music degree in Composition consists of live performances of original works composed during graduate study. The student is expected to have written and performed approximately forty-five minutes of music for various media.\nMy compositions were performed on January 27 (Autumn Fantasia) and February 20 (Five Elements) of 2006, and March 12 (Bounce!), 30 (The Little Fairy), April 3 (String Quartet No.1), August 15(Ballads of Four Seasons) and November 19 (Three Pieces for Solo Violin) of 2007.\nBriefly, each work was written in different compositional approach such as the timbres, specific colours, textures, themes and rhythmic practices. Autumn Fantasia and The Little Fairy explore the transformations and developments of thematic material. Bounce! is a piece in the procedure of tempo modulations and polyrhythmic practices. The textural experiment is the "source" for String Quartet No. 1.In both Ballads of Four Seasons and Five Elements, I employed the oriental tone color (pentatonic scales)in one particular line combining with western-based (chromaticism) sonority and sounding in other parts. Finally, to accumulate every compositional skills and techniques, Three Pieces for Solo Violin is a work binding each practices altogether.
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 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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.550 | 0.315 |
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".