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Record W4288422118 · doi:10.1016/j.ajic.2022.02.019

Methylene blue in combination with sunlight as a low cost and effective disinfection method for coronavirus-contaminated PPE

2022· article· en· W4288422118 on OpenAlexafffund
Kevin A. Vos, Paul M. K. Gordon, Belinda Heyne

Bibliographic record

VenueAmerican Journal of Infection Control · 2022
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of AlbertaBundesministerium für GesundheitWorld Health Organization
KeywordsMedicineCoronavirusHuman decontaminationCoronavirus disease 2019 (COVID-19)Methylene bluePersonal protective equipmentSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Hepatitis a virusVirologyMouse hepatitis virusSunlight2019-20 coronavirus outbreakPreparednessVirusInternal medicineOutbreakPathologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Using the Murine Hepatitis Virus (MHV) A59 coronavirus as a SARS-CoV-2 animal surrogate, we validated that methylene blue (MB) in combination with sunlight exposure is a robust, fast, and low-cost decontamination method for PPE that should be added to the toolbox of practical pandemic preparedness.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.577

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.012
GPT teacher head0.348
Teacher spread0.337 · 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 designObservational
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

Citations4
Published2022
Admission routes2
Has abstractyes

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