MétaCan
Menu
Back to cohort
Record W3016210969 · doi:10.1017/cem.2020.364

Just the Facts: Recommendations on point-of-care ultrasound use and machine infection control during the coronavirus disease 2019 pandemic

2020· article· en· W3016210969 on OpenAlexaffabout
Daniel Kim, Tomislav Jelić, Michael Y. Woo, Claire Heslop, Paul Olszynski

Bibliographic record

VenueCanadian Journal of Emergency Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsUniversity of SaskatchewanUniversity of TorontoUniversity of OttawaOttawa HospitalUniversity of ManitobaVancouver General HospitalUniversity of British Columbia
FundersChina Academy of Engineering Physics
KeywordsPandemicCoronavirusPoint of care ultrasoundCoronavirus disease 2019 (COVID-19)MedicineInfection controlDisease controlUltrasoundIntensive care medicineDisease2019-20 coronavirus outbreakHealth careSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Emergency medicineMedical emergencyVirologyInfectious disease (medical specialty)PathologyRadiologyPolitical scienceOutbreakLaw

Abstract

fetched live from OpenAlex

The World Health Organization declared the novel coronavirus disease 2019 (COVID-19) to be a pandemic on March 11, 2020, and, currently, there are over 10,000 confirmed cases in Canada, with this number expected to grow exponentially. There has been widespread interest in the use of point-of-care ultrasound (POCUS) in the management of patients with suspected COVID-19. The CAEP Emergency Ultrasound Committee has developed recommendations on the use of POCUS in these patients, with an emphasis on machine infection control measures.

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)0.019
metaresearch head score (Gemma)0.111
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.046
Threshold uncertainty score0.099

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.111
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0030.002
Science and technology studies0.0030.003
Scholarly communication0.0050.007
Open science0.0070.003
Research integrity0.0280.024
Insufficient payload (model declined to judge)0.0190.020

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 head0.167
GPT teacher head0.390
Teacher spread0.223 · 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
GenreCommentary

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

Citations42
Published2020
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Emergency MedicineSame topicUltrasound in Clinical ApplicationsFrench-language works237,207