Comparison of Four Global Sustainable Building Rating Systems Carried out With Focus on Hot and Dry Climate
Bibliographic record
Abstract
<p>Several assessment programmes has been developed worldwide on the environmental and energy effect of buildings. The aim of this study is to identify the main and sub categories of sustainable design. The researcher has investigated and compared four global building rating systems, namely leadership in Energy and Environmental Design (LEED) in USA, Emirates Green Building Rating System (ESTIDAMA) in Abu Dhabi city, Qatar Sustainability assessment System (QSAS) in the State of Qatar and Australian green Star rating system (AGBC rating system), in Australia. This paper focuses mainly on their processes, contents, similarities and differences, processes, evaluation, their development and wither these systems are applicable to all environments?</p><p>The paper outlined six main categories developed by these global rating systems being: Sustainable site, indoor environmental quality, materials, water efficiency, power supply system and innovations. Sub categories were added according to their social, cultural, economical and legislations conditions.</p>The paper recommended adding four main categories suitable to hot and dry climate.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".