Carbon Sequestering and Green Roof Technology: A Benefit Cost Analysis
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
The installation of a green roof on residential buildings affords the opportunity to sequester carbon from the atmosphere. The cost of incorporating green roofs in the construction of a family home or modifying an existing home is significant and the private benefits are rather small. Carbon reduction does have a value recognized by all levels of government in Canada. In this paper we calculate the cost of installing a green roof on a two vehicle garage in the Province of Ontario using current building costs. Utilizing data on the private costs and private benefits, the estimated NPV of a green roof over a 35 year period is negative. Once the value of carbon sequestering is introduced in the model, the NPV is positive, suggesting that subsidizing green roof construction is an efficient method in any government’s question to encourage a reduction in GHG emission.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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