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Record W4211069963 · doi:10.1098/rsfs.2021.0072

COVID-19: the case for aerosol transmission

2022· review· en· W4211069963 on OpenAlexaff
Raymond Tellier

Bibliographic record

VenueInterface Focus · 2022
Typereview
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsMcGill University
Fundersnot available
KeywordsPandemicAirborne transmissionCoronavirus disease 2019 (COVID-19)Transmission (telecommunications)PreparednessSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)AerosolOutbreakVirologyBioaerosolIndoor bioaerosolCoronavirusEnvironmental healthMedicineBiologyInfectious disease (medical specialty)MeteorologyGeographyComputer scienceDiseaseEcology

Abstract

fetched live from OpenAlex

The COVID-19 pandemic is the most severe pandemic caused by a respiratory virus since the 1918 influenza pandemic. As is the case with other respiratory viruses, three modes of transmission have been invoked: contact (direct and through fomites), large droplets and aerosols. This narrative review makes the case that aerosol transmission is an important mode for COVID-19, through reviewing studies about bioaerosol physiology, detection of infectious SARS-CoV-2 in exhaled bioaerosols, prolonged SARS-CoV-2 infectivity persistence in aerosols created in the laboratory, detection of SARS-CoV-2 in air samples, investigation of outbreaks with manifest involvement of aerosols, and animal model experiments. SARS-CoV-2 joins influenza A virus as a virus with proven pandemic capacity that can be spread by the aerosol route. This has profound implications for the control of the current pandemic and for future 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 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)0.001
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.086
GPT teacher head0.402
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

Citations96
Published2022
Admission routes1
Has abstractyes

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