Bibliographic record
Abstract
At Sea Level delves into the impacts of rising sea levels and resultant architectural responses. Countries like Vietnam, the Netherlands, Bangladesh and cities like Hamburg, New Orleans, Miami and Vancouver have been seeking to manage rising water levels and protect its residents from its potential impacts. This rise coupled with stronger storms create the perfect formula to sea level rise destruction. The first portion of this graduate project explores current flood mitigation construction categorized into 5 typologies: Elevated, Dryproofed, Floodable, Amphibious and Floating. It also delves into the phenomenology of water as a an architectural medium for hygiene, for play, and for relaxation. Five precedents were selected to investigate these methodologies and phenomenologies. The second portion of the project is presented as a story of the Vancouver Aquatic Centre located in Vancouver, Canada. Through a collection of real and mythic historical evidence, a narrative loop traversing through both a family’s history and that of greater culture is set against the context of an aging piece of civic infrastructure. Under siege from rising sea levels, the building transforms in response to environmental and social conditions over a 180 year period to allow for water to be perceived as something beautiful; reinforcing architecture’s capability to re-frame something that is feared into something that is valued. Water was used to enhance experiences as opposed to abandoning them. Water was the protagonist.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.294 | 0.107 |
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".