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Record W7132399028

Determining inter-zonal flow rates using passive sampling of tracer gases

2020· article· en· W7132399028 on OpenAlexaffvenue
Doyun Won, Wenping Yang, Stephanie So, Gang Nong

Bibliographic record

VenueNPARC · 2020
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsTRACERSampling (signal processing)Passive samplingVentilation (architecture)AirflowVolumetric flow rateSampling time
DOInot available

Abstract

fetched live from OpenAlex

Whole-house and inter-zonal ventilation rates are important parameters to understand energy efficiency and indoor air quality. Under occupancy, passive sampling using thermal desorption (TD) tubes is more desirable due to its simple and less obtrusive nature. In this research, the uptake rates of six perfluoro-carbon tracer (PFT) gases were determined in a laboratory setting for 4 to 7-day passive sampling on two types of TD tubes. The sources of PFTs were manufactured and their stability were investigated for 4 months. The passive method was validated against the SF₆ decay method and applied to determine inter-zonal air flows in a research house. The air change rates measured with the passive release and sampling of PFT gases were comparable to those from the SF₆ method. This study shows that the passive uptake rates determined in a chamber and PFT sources manufactured in-house can be useful to measure the inter-zonal air flows in homes under occupancy.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.072
GPT teacher head0.330
Teacher spread0.258 · 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 designBench or experimental
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
Published2020
Admission routes2
Has abstractyes

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Same venueNPARCSame topicInfection Control and VentilationFrench-language works237,207