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Record W4293089125 · doi:10.1017/ice.2022.195

Mitigating healthcare staffing shortages: Should healthcare workers with severe acute respiratory coronavirus virus 2 (SARS-CoV-2) household exposures work?

2022· article· en· W4293089125 on OpenAlexaffabout
Ana C. Blanchard, Valérie Lamarre, Josée Lamarche, Nathalie Audy, Caroline Quach

Bibliographic record

VenueInfection Control and Hospital Epidemiology · 2022
Typearticle
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsMedicineHealth carePersonal protective equipmentStaffingAsymptomaticCoronavirusSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Emergency medicineVirologyCoronavirus disease 2019 (COVID-19)Internal medicineDiseaseInfectious disease (medical specialty)Nursing

Abstract

fetched live from OpenAlex

In a tertiary-care, pediatric healthcare center in Québec, Canada, healthcare workers who reported a household exposure to confirmed coronavirus disease 2019 (COVID-19) cases were allowed to work. On repeated testing, 15% became severe acute respiratory coronavirus virus 2 (SARS-CoV-2)-positive by reverse-transcription polymerase chain reaction (RT-PCR), with no nosocomial transmission. Being asymptomatic and receiving a booster dose >7 days prior to exposure was protective against becoming SARS-CoV-2-positive by PCR.

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 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)0.004
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.078
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.267
GPT teacher head0.424
Teacher spread0.157 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations3
Published2022
Admission routes2
Has abstractyes

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