Learned Lessons from Traditional Architecture in Yemen -Towards Sustainable Architecture
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
This paper explores the Learned Lessons from traditional Yemeni Architecture Towards Sustainable Architecture. It highlights how the local context influences the traditional architecture in Sanaa city and different regions of Yemen and Arab regions, according to nature, climatic conditions, culture, traditional values, and indigenous knowledge. Overview for sustainability during the twentieth century, sustainability and the Islam perspective in the Arab region, and selected the traditional architecture in Yemen as a case study. In addition to the analysis analyzed the city's urban form and the traditional house in Sana’a city, the design and elements of the house; spatial organization, construction systems and building materials, and window openings. Ornaments and sewerage systems. The study summarizes the aspects of sustainability in the traditional house in different regions in Yemen as an indigenous traditional knowledge for sustainable architecture. In conclusion, the traditional houses in the house in Yemen, designed according to the local context and indigenous traditional knowledge, have influenced traditional Yemeni architecture; the house elements and design fulfills sustainable requirements and positively impact the city's environmental, economic, and social aspects. Furthermore, it is considered a learned lesson from traditional architectural heritage and indigenous traditional knowledge toward sustainable architecture.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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