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Record W3115880106 · doi:10.1080/01919512.2020.1839739

Critical Review and Research Needs of Ozone Applications Related to Virus Inactivation: Potential Implications for SARS-CoV-2

2020· article· en· W3115880106 on OpenAlexaff
Christina M. Morrison, Ariel J. Atkinson, Arash Zamyadi, Faith A. Kibuye, Michael J. McKie, Samantha Hogard, Phil J Mollica, Saad Jasim, Eric C. Wert

Bibliographic record

VenueOzone Science and Engineering · 2020
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)OzoneSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)VirusEnvironmental scienceMedicineBusinessVirologyChemistryInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Ozone disinfection has demonstrated high efficacy against enveloped and non-enveloped viruses, including viruses similar in morphology to SARS-CoV-2. Due to this efficacy, numerous gaseous and aqueous phase ozone applications have emerged to potentially inhibit virus persistence in aerosols, surfaces, and water. This review identifies the exposure requirements for virus inactivation and important safety considerations for applications within the built environment (i.e. occupied/unoccupied spaces, air/water/wastewater treatment) and healthcare settings (i.e. ozone therapy, dentistry, handwashing, treatment of personal protection equipment (PPE)). Current research needs are presented to advance the utilization of ozone as a mitigation strategy.

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)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0060.001

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 head0.064
GPT teacher head0.379
Teacher spread0.316 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations54
Published2020
Admission routes1
Has abstractyes

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