Can “EDGE” be the Solution to Sustainability of Buildings in Colombian Market?
Bibliographic record
Abstract
Traditional energy efficiency certificates for buildings, such as LEED (Leadership in Energy and Environmental Design), in spite of their worldwide success, have not yet gained the expected penetration in some developing (and less-developed) countries. Some factors contributing to such a trend include cost, complexity, and demand for new resources that may not be always available. In an effort to aid the building sector, the World Bank, which is one of the principal carbon emissions productive sectors and the user of a big amount of resources that implies high energy and water consumption, has developed a new tool called EDGE (Excellence in Design for Greater Efficiencies). This paper aims to examine the capabilities of EDGE and test if it can have qualities and features required to gain more momentum for energy upgrade in the building sector within developing countries. According to its proposal, EDGE is low-cost; has a user-friendly software to apply; and a “do-it-yourself” nature. We have focused on Colombian building construction market, and have investigated the opportunities for EDGE in three dimensions of: cost, operability, and penetrability. The opinion of energy rehabilitation and construction experts in Colombian building industry was mined through survey questionnaires and studied through a detailed qualitative and quantitative analysis of requirements for applying EDGE to building projects. Through analysis of the experts’ inputs, the paper aims to evaluate the success chance of such simplified methods in the Colombian building market.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".