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Record W4235664713 · doi:10.5383/ijtee.11.01.006

Performance of World Health Organization as a Green Building

2016· article· en· W4235664713 on OpenAlexvenueno aff
Kholoud Hassouneh, Ahmed Al‐Salaymeh, Ahmad Sakhrieh

Bibliographic record

VenueInternational Journal of Thermal and Environmental Engineering · 2016
Typearticle
Languageen
FieldEnergy
TopicEnergy Efficiency and Management
Canadian institutionsnot available
Fundersnot available
KeywordsHVACEnergy consumptionArchitectural engineeringEfficient energy useConsumption (sociology)Greenhouse gasElectricityBuilding codeEnvironmental economicsBusinessGreen buildingCivil engineeringEngineeringAir conditioningEconomics

Abstract

fetched live from OpenAlex

The rapidly growing world energy use has already raised concerns over supply difficulties, exhaustion of energy resources and heavy environmental impacts. The global contribution from buildings towards energy consumption has steadily increased. Jordan relying on importing more than (97%) of its oil needs. The household in Jordan consumes 43% of the total electricity produced. The current situation enforces us to have more efficient use of energy in this sector. For this reason, energy efficiency in buildings is today a prime objective for energy policy at national and international level. The Jordanian buildings codes such as the Jordan green building code were developed to face energy challenges that Jordan has recently encountered. In residential sector, energy is used for equipment and appliances that provide heating, cooling, lighting, water heating, and other household demands. In this study, an efficient energy building has been selected and studied. The present study concentrates on the one of the energy saving examples, which is Green building represented in the World Health Organization (WHO) building in Amman. A comprehensive study of energy consumption in the building has been carried out. A comparison between the Jordanian regular buildings and the current building was made; EnergyPlus was used to make all calculations. It is found that the WHO building saves 23.9% of the total energy saved from HVAC systems, and widely dependent on the natural lighting. WHO reduces the Greenhouse gases emissions of CO2, about 57563.12 kg of CO2 were reduced, which helps in the global warming.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0120.002

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 head0.003
GPT teacher head0.180
Teacher spread0.177 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2016
Admission routes1
Has abstractyes

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