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Record W4392291850 · doi:10.18280/ijdne.190138

Greening Conservation Buildings in Light of Contemporary Technology: The Iraqi Conservation Experience

2024· article· en· W4392291850 on OpenAlexvenueno aff
Taiser Ehsan Jabar, Enas Salim Abdulahaad

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2024
Typearticle
Languageen
FieldArts and Humanities
TopicConservation Techniques and Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGreeningArchitectural engineeringEnergy conservationGeographyEngineeringEnvironmental resource managementEnvironmental scienceEcologyBiologyElectrical engineering

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.791
Threshold uncertainty score0.269

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.275
Teacher spread0.245 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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