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Record W4311582290 · doi:10.1038/s41597-022-01860-y

Particle filtration efficiency measured using sodium chloride and polystyrene latex sphere test methods

2022· article· en· W4311582290 on OpenAlexafffund
Timothy A. Sipkens, Joel C. Corbin, Andrew Oldershaw, Gregory J. Smallwood

Bibliographic record

VenueScientific Data · 2022
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsNational Research Council Canada
FundersPublic Health AgencyPublic Health Agency of Canada
KeywordsPolystyreneDispersityFiltration (mathematics)Materials scienceSodiumEquivalence (formal languages)ChlorideParticle sizeParticle (ecology)MathematicsChemistryPolymer chemistryStatisticsComposite materialMetallurgyPhysical chemistry

Abstract

fetched live from OpenAlex

Standards governing face masks differ in the test methods used to determine sub-micron particle filtration efficiency (PFE), such that the meaning of PFE is not universal. Unifying the meaning of PFE requires data using these different test methods to drive improvements in standards. This simple data set provides the equivalence between two major test methods used to assess PFE: (1) a test method using a neutralized, polydisperse sodium chloride (NaCl) and (2) a test method using an unneutralized, "monodisperse" polystyrene latex sphere (PSL) aerosols. Measurements are made on over 5800 real-world medical masks, leading to the establishment of a relationship between these two kinds of PFE for these products.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.003
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.099
GPT teacher head0.365
Teacher spread0.266 · 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

Citations13
Published2022
Admission routes2
Has abstractyes

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