Bibliographic record
Abstract
Faraday Waves is a short audio-visual work written as a companion piece for a concert-hall performance of Poeme electronique by Varese. Faraday discovered that a liquid undergoing vertical vibration, whose frequency exceeds a certain value, becomes unstable to surface waves. Also known as Faraday Instability, they form non-linear standing waves that appear on liquids enclosed by a vibrating vessel. In ordinary Newtonian fluids (those that do not exhibit shear thickening or shear thinning) the wave patterns include ones with 1-fold symmetry (stripes), 2-fold symmetry (squares), 3-fold symmetry (hexagons) as well as higher orders of symmetry. The effect was first reported by Michael Faraday in 1831, and forms one of many experiments in visualizing vibration and sound -- a means of converting analogue data from one form to another. Thanks to an award from Santander, Rob was able to visit his colleague Professor Stephen Morris at the Physics Department, University of Toronto in May 2015. Part of Stephen's research regards 'shaking things' and sound is often used as a form of stimuli. The visualization, created by Sam Jury, uses video documentation of the classic physics experiment invented by Faraday with the analogy of sound to image data transfer used as the starting point for the creation of the music. Faraday Waves uses speech rhythms found in the e.e. cummings poem I Carry Your Heart With Me. Placed within the resonance of a bell; it symbolizes the creation and birth of a new life.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.123 | 0.055 |
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".