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Record W4319826880 · doi:10.1093/cid/ciad068

Coronavirus Disease 2019 and Airborne Transmission: Science Rejected, Lives Lost. Can Society Do Better?

2023· article· en· W4319826880 on OpenAlex
Lídia Morawska, William P. Bahnfleth, Philomena M. Bluyssen, Atze Boerstra, Giorgio Buonanno, Stephanie J. Dancer, R. Andrés Floto, F. Franchimon, Charles Haworth, Jaap Hogeling, Christina Isaxon, J. L. Jiménez, Jarek Kurnitski, Yuguo Li, Marcel Loomans, Guy B. Marks, Linsey C. Marr, Livio Mazzarella, Arsen Krikor Melikov, Shelly L. Miller, Donald K. Milton, William W. Nazaroff, Peter V. Nielsen, Catherine J. Noakes, Jordan Peccia, Xavier Querol, Chandra Sekhar, Olli Seppänen, Shin‐ichi Tanabe, Raymond Tellier, Pawel Wargocki, Aneta Wierzbicka

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Infectious Diseases · 2023
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsMcGill University
FundersNational Institute of Environmental Health SciencesNational Institute of Allergy and Infectious DiseasesFlu Lab
KeywordsCoronavirus disease 2019 (COVID-19)MedicineSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakTransmission (telecommunications)PandemicCoronavirusVirologyCoronavirus InfectionsBetacoronavirusAirborne transmissionDisease transmissionDiseaseInfectious disease (medical specialty)OutbreakPathologyTelecommunications

Abstract

fetched live from OpenAlex

This is an account that should be heard of an important struggle: the struggle of a large group of experts who came together at the beginning of the COVID-19 pandemic to warn the world about the risk of airborne transmission and the consequences of ignoring it. We alerted the World Health Organization about the potential significance of the airborne transmission of SARS-CoV-2 and the urgent need to control it, but our concerns were dismissed. Here we describe how this happened and the consequences. We hope that by reporting this story we can raise awareness of the importance of interdisciplinary collaboration and the need to be open to new evidence, and to prevent it from happening again. Acknowledgement of an issue, and the emergence of new evidence related to it, is the first necessary step towards finding effective mitigation solutions.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.053
GPT teacher head0.389
Teacher spread0.336 · 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