The effect of Changing Construction Materials on Historical Building Performance in Case of Restoration - Case Study of Al-Nabi Jirjis Mosque in Old Mosul City
Bibliographic record
Abstract
Choosing appropriate construction materials in restoration processes of historical buildings particularly after wars or disasters is crucial in retaining the importance of such buildings and their distinct characteristics.This study is to explore how a change of original construction materials can influence energy efficiency and thermal comfort when rebuilding the destroyed historic buildings after the war in Old Mosul, where Al-Nabi Jrjis Mosque was selected as a case study.The study has adopted a comparative method between three simulation scenarios including two sets of new materials in addition to the original one.ENVI met analysis is used as a method to simulate the three cases.Results showed that the original set of materials (stone and plaster) has characterized by the best thermal efficiency compared by new materials used in the study.However, a set of hollow concrete with PVC strip used in one of the other scenarios revealed somehow good results, which therefore can be used as an acceptable alternative if the original materials are not available.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".