684: From the Modern toit jardins to the current green roofs: can a hit become classic?
Bibliographic record
Abstract
What do builders think regarding the use of vegetation on roofs? The present paper looks for an answer in Brazil, a country where the technology still does not show an expressive development, even in the city known as its “ecological capital”, Curitiba. It should be stressed that the technology of using vegetation on roofs carries the impressions of at least two moments in the History of Architecture: first, the ancient use in the hanging gardens of Babylon and the turf houses from Island; and second, their dissemination in the early 20th Century within the Modern Movement in Architecture with Le Corbusier's toit jardin (besides free plans, free facades, pilotis and fenetre-en-longueur, one of the five points in his Architecture). But nowadays, in the so-called green roofs- name adopted in the Northern Hemisphere – a mature technology can be recognized. Its long evolution is well-known: several implementation problems could be overcome, due to the efforts of a still growing industry particularly in Germany, Canada and the USA. In addition, several factors contribute to a renewed interest for that choice: one should mention high land prices in cities, soil insulation and its effects, and urban heat islands; as well, the pledge for a reduction in energy consumption of buildings and the lack of urban green areas. Nevertheless, the dissemination of such a design strategy seems as difficult a task as it was its technological development. Whereas successful
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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 | 0.002 |
| 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 | 0.009 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".