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Record W3093764202 · doi:10.1128/jcm.02593-20

Comparison of Upper Respiratory Viral Load Distributions in Asymptomatic and Symptomatic Children Diagnosed with SARS-CoV-2 Infection in Pediatric Hospital Testing Programs

2020· article· en· W3093764202 on OpenAlexaff
Larry K. Kociolek, William J. Muller, Rebecca Yee, Jennifer Dien Bard, Cameron A. Brown, Paula A. Revell, Hanna Wardell, Timothy J. Savage, Sarah Jung, Samuel R. Dominguez, Bijal A. Parikh, Robert C. Jerris, Sue C. Kehl, Aaron Campigotto, Jeffrey M. Bender, Xiaotian Zheng, Emily Muscat, Matthew Linam, Lisa Abuogi, Christiana Smith, Kelly Graff, Ariel Hernandez-Leyva, David N. Williams, Nira R. Pollock

Bibliographic record

VenueJournal of Clinical Microbiology · 2020
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsAsymptomaticMedicineSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Viral loadRespiratory systemCoronavirus disease 2019 (COVID-19)PediatricsLiterInternal medicineVirologyVirusDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

The distribution of upper respiratory viral loads (VL) in asymptomatic children infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is unknown. We assessed PCR cycle threshold (Ct) values and estimated VL in infected asymptomatic children diagnosed in nine pediatric hospital testing programs. Records for asymptomatic and symptomatic patients with positive clinical SARS-CoV-2 tests were reviewed. Ct values were (i) adjusted by centering each value around the institutional median Ct value from symptomatic children tested with that assay and (ii) converted to estimated VL (numbers of copies per milliliter) using internal or manufacturer data.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.011
Threshold uncertainty score0.641

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.093
GPT teacher head0.428
Teacher spread0.334 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations104
Published2020
Admission routes1
Has abstractyes

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