MétaCan
Menu
Back to cohort
Record W4377289938 · doi:10.12809/hkmj209089

Mitigation of COVID-19 transmission in endoscopic and surgical aerosol-generating procedures: a narrative review of early-pandemic literature

2023· review· en· W4377289938 on OpenAlexaff
Vinson Wai‐Shun Chan, Laiba Rahman, Helen HL Ng, KP Tang, Alex Mok, Audrey Tang, Jeremy PH Liu, Kenny SC Ho, Shannon M. Chan, Sunny H. Wong, Anthony Yuen Bun Teoh, Albert Kam Ming Chan, Martin C. S. Wong, Yuhong Yuan, Jeremy Yuen‐Chun Teoh

Bibliographic record

VenueHong Kong Medical Journal · 2023
Typereview
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsMcMaster University
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)PandemicMedicine2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)NarrativeTransmission (telecommunications)AerosolMedical emergencyVirologyMeteorologyInternal medicineGeographyComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

Literature search and evidence acquisitionA comprehensive literature search was performed using a combination of keywords (MeSH terms and free text words) including 'COVID-19'/ 'SARS-CoV*'/'SARS'/'MERS' , 'aerosol' , 'surgery' , 'operation/procedure' , 'endoscopy' , and 'healthcare workers' .MEDLINE, Embase, the Cochrane Database of Systematic Reviews, and the Cochrane Central Register of Controlled Trials were searched up to 18 July 2020.Preprint servers, medRxiv, and bioRxiv were also searched for information up to that date.The search was limited to studies published during or after 2003, when the SARS outbreak began.

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)0.006
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.019
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0130.011
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.001
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 head0.091
GPT teacher head0.461
Teacher spread0.371 · 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 designSystematic review
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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueHong Kong Medical JournalSame topicCOVID-19 and healthcare impactsFrench-language works237,207