MétaCan
Menu
Back to cohort

The Determination of the Rapid and Effective Activity of an Air Sanitizer against Aerosolized Bacteria Using a Room-Sized Aerobiology Chamber

2024· article· en· W4403459994 on OpenAlexaff
Bahram Zargar, M. Khalid Ijaz, Anthony Kevek, Mark A. Miller, Julie McKinney, Syed A. Sattar

Bibliographic record

VenueMicroorganisms · 2024
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsAerosolizationAerobiologyHand sanitizerEnvironmental scienceMicrobiologyVirologyBiologyInhalationFood science

Abstract

fetched live from OpenAlex

Air sanitization is an important non-pharmaceutical intervention for mitigating the risk of indoor pathogen spreading. A dipropylene glycol-containing air sanitizer was tested against aerosolized Staphylococcus aureus and Klebsiella pneumoniae. The bacteria, suspended in a soil load, were aerosolized using a six-jet Collison nebulizer with pressurized air. The 25-m3 (~900 ft3) aerobiology chamber was maintained at 22 ± 2 °C and 50 ± 5% relative humidity per the U.S. Environmental Protection Agency’s 2012 Guidelines on air sanitizers. An initial 2-min air sample was collected from the chamber using a slit-to-agar sampler containing 150-mm Petri plates, with Trypticase soy agar (TSA) containing neutralizers to quench the microbicidal activity of the air sanitizer, to determine the initial bacterial challenge in the air. The air sanitizer was sprayed into the chamber from pressurized cans. Additional air samples were collected from the chamber over 10 min to detect surviving bacteria. The TSA plates were then incubated aerobically at 36 ± 1 °C for 90 ± 4 h and scored for bacterial colony-forming units. A 30-s spray of the air sanitizer reduced infectious S. aureus and K. pneumoniae titers by 3.0 log10 (99.9%) in 3.2 ± 0.3 min and 1.2 ± 0.0 min, respectively. Based on these findings, the EPA granted registration of the air sanitizer as the first product of its kind for indoor air sanitization.

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)0.000
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 score0.072
Threshold uncertainty score0.250

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 head0.009
GPT teacher head0.259
Teacher spread0.250 · 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.

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

Citations5
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueMicroorganismsSame topicInfection Control and VentilationFrench-language works237,207