Performance evaluation of an extensive green roof
Bibliographic record
Abstract
This study aims to provide technical data on the performance of green roofs in the City of Toronto, and to illustrate their benefits in an urban context. Two extensive green roof systems were installed on a community centre in Toronto. Both systems contained the same components that differed in materials and designs. The green roofs contained lightweight growing medium, 75 - 100 mm in depth, that supported a variety of vegetation. The green roofs, and a reference roof, were instrumented to provide thermal performance and energy efficiency data, as well as runoff measurements. Although the vegetation was not well established in the first year of monitoring, nevertheless, the extensive green roofs reduced the building's energy demand by lowering the heat flow through the roof, especially in the summer. The green roofs were shown to be effective in delaying and reducing stormwater runoff and the retentionefficiency depended upon the characteristics of the rain event (intensity and amount) and the wetting history of the growing medium. Preliminary observations and membrane temperatures recorded also suggest that green roofs could likely improve membrane durability by reducing heat aging, thermal stresses, ultra-violet radiation and physical damages.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".