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Record W4403769272 · doi:10.1016/j.lanmic.2024.101012

Blood transcriptomic analyses do not support SARS-CoV-2 persistence in patients with post-COVID-19 condition with chronic fatigue syndrome

2024· letter· en· W4403769272 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueThe Lancet Microbe · 2024
Typeletter
Languageen
FieldMedicine
TopicLong-Term Effects of COVID-19
Canadian institutionsWomen and Children’s Health Research InstituteUniversity of Alberta
FundersInstitute of Infection and ImmunityLi Ka Shing Institute of Virology, University of Alberta
KeywordsPersistence (discontinuity)Coronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)2019-20 coronavirus outbreakMedicineVirologyBetacoronavirusPandemicInternal medicineDiseaseInfectious disease (medical specialty)Outbreak

Abstract

fetched live from OpenAlex

Post-COVID-19 condition (also known as long COVID) represents a crucial and emerging global public health challenge. Intriguingly, growing claims exist about the persistence of SARS-CoV-2 or viral antigens in the blood and tissues of patients with long COVID for months after the acute infection. This occurrence is not exclusive to SARS-CoV-2 as long-term shedding of influenza A virus in the stool of immunocompromised patients has been reported previously.1 Furthermore, this finding corresponds with that of a previous report that at 2 months following acute COVID-19, viral RNA was detected in various solid tissues and peripheral blood of immunocompromised individuals with post-COVID-19 symptoms, as opposed to that in immunocompetent individuals.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.252
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
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 head0.046
GPT teacher head0.322
Teacher spread0.276 · 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