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Record W4283737438 · doi:10.1002/jbio.202200068

Generalized <scp>Kubelka's</scp> theory for light transmission in multilayer materials and its application for <scp>UV</scp> light penetration in filtering facepiece respirators

2022· article· en· W4283737438 on OpenAlexaff
Ramin Farnood, Housyn Mahmoud, John Gibson, Ted Mao, Conrad Odegaard

Bibliographic record

VenueJournal of Biophotonics · 2022
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsShared HealthUniversity of Toronto
Fundersnot available
KeywordsRespiratorTransmittanceUltravioletIrradianceMaterials scienceOpticsPenetration (warfare)IrradiationAbsorbanceEconomic shortageOptoelectronicsTransmission (telecommunications)Penetration depthComputer sciencePhysicsComposite materialTelecommunicationsMathematics

Abstract

fetched live from OpenAlex

The spread of SARS-CoV-2 has resulted in the shortage of filtering facepiece respirators (FFRs). As a result, the use of ultraviolet (UV) irradiation for disinfection and reuse of FFRs has been the topic of much investigation. In this article, a mathematical model is developed based on Kubelka's theory to determine light transmission in multilayer materials, such as N95 masks. Using this model, the predicted UV transmittance and absorbance of a N95 mask layers were found to be in close agreement with the experimental values. In addition, when the mask was exposed to UV equally from both surfaces, the estimated minimum UV irradiance inside the N95 mask was 14.5% of the incident irradiance, suggesting a significant degree of light penetration. The proposed model provides a simple and practical methodology for the design and use of UV decontamination equipment for FFRs and other multilayer materials.

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)0.000
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 score0.109
Threshold uncertainty score0.616

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.016
GPT teacher head0.277
Teacher spread0.261 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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