MétaCan
Menu
Back to cohort
Record W3037471384 · doi:10.1080/23744731.2020.1787085

Performance of mechanical filters used in general ventilation against nanoparticles

2020· article· en· W3037471384 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueScience and Technology for the Built Environment · 2020
Typearticle
Languageen
FieldEngineering
TopicAerosol Filtration and Electrostatic Precipitation
Canadian institutionsInstitut de recherche Robert-Sauvé en santé et en sécurité du travailConcordia University
FundersConcordia UniversityInstitut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail
KeywordsASHRAE 90.1Pressure dropMaterials scienceFiltration (mathematics)NanoparticleParticle sizePenetration (warfare)Composite materialNanotechnologyChemical engineeringMechanicsMathematicsEngineeringPhysicsStatistics

Abstract

fetched live from OpenAlex

With an equal mass, nanoparticles (NP) have a higher toxicity than particles with the same chemical composition but with larger surface area. However, the toxicological knowledge concerning NP is still insufficient to establish limit values of exposure. To seek the lowest exposure level, filtration is a simple and effective way to capture particles, including NP. According to ANSI/ASHRAE 52.2 standard, ventilation filters efficiency is tested for particles ranging from 0.3 to 10.0 μm. Performances of entire filters for NP are still very limited and particle size of 300 nm (0.3 μm) is commonly used as the most penetrating particle size (MPPS) for mechanical media. To evaluate the filter performance for NP, five type of filters were investigated to measure their performance for particles smaller than 300 nm including NP. The performance of these filters was evaluated in terms of penetration and pressure drop. Experimental data permit to evaluate the MPPS for these mechanical filters. Nevertheless, 150–500 nm range provides a better estimation of the MPPS in the conditions which were tested. Also, filtration velocity influences efficiency for nanoparticles at 50 nm but no effect was observed for MPPS.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.415
Threshold uncertainty score0.128

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 head0.014
GPT teacher head0.208
Teacher spread0.194 · 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