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Identifikasi dan Evaluasi Pengaruh Ventilasi Alami pada Ruang Kelas Terhadap Fenomena Sick Building Syndrome

2023· article· en· W4389286123 on OpenAlexaff
Latifah Latifah, Ratih Widiastuti

Bibliographic record

VenueJurnal Sipil dan Arsitektur · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSustainability, Governance, and Employment Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsSick building syndromeNatural ventilationVentilation (architecture)Air conditioningArchitectural engineeringEnvironmental scienceIndoor air qualityMeteorologyEngineeringGeographyEnvironmental engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Natural ventilation is closely related to the indoor air quality and will affect the occupant activities. The unhealthy air conditioning will create discomfort for the occupants. One of the phenomena that is caused by indoor air quality is Sick Building Syndrome (SBS). Bad air circulation systems in the classroom can lead to Sick Building Syndrome (SBS) among students. This study was conducted to identify and evaluate the influence of natural ventilation in the classroom on the Sick Building Syndrome phenomenon. The object of the study was classrooms in the Department of Architecture, Faculty of Engineering, Diponegoro University. Data of temperature, relative humidity, and air velocity were collected to identify the indoor air quality of the classrooms. Based on the analysis, either with closed or open natural ventilation, the indoor air quality inside the classroom still did not meet the requirement of healthy air. Therefore, further actions such as improving the quality of natural ventilation are needed.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.318
Teacher spread0.288 · 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.

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
Published2023
Admission routes1
Has abstractyes

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