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Record W2800594092 · doi:10.3390/su10051565

Passive Ventilation for Indoor Comfort: A Comparison of Results from Monitoring and Simulation for a Historical Building in a Temperate Climate

2018· article· en· W2800594092 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSustainability · 2018
Typearticle
Languageen
FieldEngineering
TopicSolar Energy Systems and Technologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsNatural ventilationVentilation (architecture)Environmental scienceArchitectural engineeringAir conditioningSustainabilityMeteorologyEngineeringEcologyGeography

Abstract

fetched live from OpenAlex

When environmental sustainability is a key feature of an intervention on a building, the design must guarantee minimal impact and damage to the environment. The last ten years have seen a steady increase in the installation of highly efficient systems for winter heating, but this trend has not been mirrored for summer cooling systems. Passive ventilation, however, is a means of summer air conditioning with a low financial and environmental impact. Natural ventilation methods such as “wind towers” have been used to achieve adequate levels of internal comfort in buildings. However, the application of these systems in old town centres, where buildings are often of great architectural value, is complex. This study started with the analysis of various ventilation chimneys in order to identify the most suitable system for temperate climes. Ventilation systems were then designed using static analysis of ventilation with specific software, and installed. The results were assessed and monitored using climatic sensors over the summer period, in order to establish the period of maximum functionality to optimize the system’s performance.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.588
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.021
GPT teacher head0.309
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