Greening Conservation Buildings in Light of Contemporary Technology: The Iraqi Conservation Experience
Bibliographic record
Abstract
The research focuses on the concept of green conservation, which means integrating advanced technological capabilities within conservation buildings in accordance with both conservation standards and green architecture standards, with the aim of revitalizing and upgrading buildings of value.Upon review of the Iraqi Green Code, it was found that it excludes conservation buildings, which identified the problem of the research in the absence of a trend towards greening local conservation buildings.The goal of the research was determined by the necessity of presenting a theoretical framework for greening conservation buildings in light of the specificity of the local context, which could serve as an approach for specialists on the one hand and to activate the Iraqi Code on the other hand.The research adopted the descriptive approach, which included a set of steps in order to reach a theoretical framework that includes major and secondary vocabulary through (clarifying green technological techniques -analyzing studies and specialized literature -analyzing the practices of the concept within the Arab context -analyzing the indicators of the Iraqi Green Code) so that the research moves to the next step.The following is represented by applying the vocabulary of the framework to the Baghdadi Museum building (where the Baghdad Municipality completed maintenance and preservation operations in a way that preserves its value and prevents its deterioration) to apply the vocabulary of the theoretical framework to reach the conclusions that confirmed the power of technological capabilities in upgrading the Baghdadi Museum building and raising its efficiency without compromising its original features.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".