The architecture of phase change at McGill
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Montreal has a history of monumental ice construction dating back to 1885 when the first large-scale ice palace was constructed for the winter carnival.At McGill University, we have experimented with large-scale ice construction since 1972.In addition to the use of traditional ice blocks, we have built composite structures using suspended nylon fabric as a substrate for depositing vaporized water in the freezing winter conditions.Our largest structure was a scale model of the Pantheon, built with snow, and spanning 34 ft.Robotic CNC and rapid prototyping (RP) methods are opening up new horizons for the water-to-ice phase change process in architecture.Since 2006, we have been working at three different scales in this field, funded by a 3 year $174 000 SSHRC grant.A small Fab@Home rapid prototyping machine has been modified to make small 3D ice objects in a -20C environment.One scale up, we are now working with an Adept Cobra 600 robot, producing very finely detailed 3D ice objects up to 30 cm across and 20 cm high.Both these machines are controlled by a personal computer and rely on a water delivery system with micro-valves, adapted for the purpose.The different melting temperatures of brine and pure water make it possible to use brine as scaffolding for the ice model, since the frozen brine can be melted away at a lower temperature than the ice.In 2010, we hope to scale up again, this time to the architectural scale with a new Macro robot.Conference theme: Digital approaches to architectural design and education
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it