Green roof research in British Columbia - an overview
Bibliographic record
Abstract
In 2002 a stakeholder workshop held in Vancouver identified the major barriers to the market penetration of green roofs in BC as the lack of climate-specific performance data, the absence of third party testing and verification of green roof systems, and a lack of demonstrated feasibility. To address these issues the British Columbia Institute of Technology (BCIT), supported by a consortium of regional government organizations, industry associations, and material suppliers, created a green roof research program. In collaboration with the National Research Council of Canada (NRC), a dedicated field test site, the Green Roof Research Facility (GRRF) was constructed and commissioned in 2003. This presentation will discuss BCIT's educational strategy in green roof technology, design and construction of the facility, instrumentation for data collection, and preliminary data. BCIT has expanded its capacity to create the Centre for the Advancement of Green Roof Technology (CAGRT). The Centre's principle functions within the education and research forum are to develop the regional infrastructure network to inventory performance of green roofs; develop a system performance evaluation module, provide a testing and verification facility for the local green roof industry, and improve public awareness of the technology through education and demonstration.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.013 | 0.026 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".