Bibliographic record
Abstract
Hoodoos was composed from sound materials recorded along the Hoodoo Trail in Banff National Park in the Rocky Mountains of Western Canada. It is concerned with contrasting states of dynamic, fluidity, stasis, and kinesis. Accordingly, the sound of ice is present in frozen, cracking, melting, and shattering forms. Water coalesces into murky icy depths, drips and freely flows. Wood creaks, smoulders, breaks, and grows. Everything stirs, from the microscopic to the larger scale. The snow is unstable- avalanches and landslides are frequent. The great fluctuations of spring bring great change to the mountain valley- the quality (and quantity) of light evolves and accompanies growing activity and tension as the environment is released from its winter freeze and darkness. Hoodoos also refers to unique geological formations found in the Badlands regions of North America that are highly eroded spires of sedimentary rock, alien and exotic in appearance. Hoodoos was composed for the Flux Sound Diffusion System developed by the composer to allow for greater variability in the live performance of fixed-media works.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.132 | 0.024 |
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".