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Record W2769907034 · doi:10.1016/j.ebiom.2017.10.021

Corrigendum to “Zika Virus Causes Persistent Infection in Porcine Conceptuses and May Impair Health in Offspring”

2017· erratum· en· W2769907034 on OpenAlexaff
Joseph Darbellay, Brian Cox, Kenneth Lai, Mario Delgado-Ortega, Colette Wheler, D. Wilson, Stewart Walker, Gregory Starrak, Duncan K. Hockley, Yanyun Huang, George Mutwiri, Andrew Potter, Matthew W. Gilmour, David Safronetz, Volker Gerdts, Uladzimir Karniychuk

Bibliographic record

VenueEBioMedicine · 2017
Typeerratum
Languageen
FieldMedicine
TopicCOVID-19 Impact on Reproduction
Canadian institutionsPublic Health Agency of CanadaDiagnostic Services ManitobaUniversity of TorontoUniversity of Saskatchewan
Fundersnot available
KeywordsZika virusOffspringIn uteroAsymptomaticMedicineConfusionPregnancyPediatricsFetusVirologyVirusObstetricsBiologyPathologyPsychologyGenetics

Abstract

fetched live from OpenAlex

An earlier online version of the paper contained an error in the bioinformatics data tables. This error has now been corrected by the authors, and the changes in the tables and corresponding text have been verified with a reviewer. The online version of the paper has now been updated to include this correction. We apologize for the confusion. Zika Virus Causes Persistent Infection in Porcine Conceptuses and may Impair Health in OffspringOutcomes of Zika virus (ZIKV) infection in pregnant women vary from the birth of asymptomatic offspring to abnormal development and severe brain lesions in fetuses and infants. There are concerns that offspring affected in utero and born without apparent symptoms may develop mental illnesses. Therefore, animal models are important to test interventions against in utero infection and health sequelae in symptomatic and likely more widespread asymptomatic offspring. To partially reproduce in utero infection in humans, we directly inoculated selected porcine conceptuses with ZIKV. Full-Text PDF Open Access

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.327
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.064
GPT teacher head0.376
Teacher spread0.312 · 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 designNot applicable
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

Citations1
Published2017
Admission routes1
Has abstractyes

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