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Record W2117005158 · doi:10.1002/jmv.24410

2014 outbreak of enterovirus D68 in North America

2015· review· en· W2117005158 on OpenAlexaboutno aff
Kevin Messacar, Mark J. Abzug, Samuel R. Dominguez

Bibliographic record

VenueJournal of Medical Virology · 2015
Typereview
Languageen
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsnot available
Fundersnot available
KeywordsOutbreakEnterovirusVirologyPicornavirusMedicinePublic healthMyelitisFlaccid paralysisPediatricsParalysisVirusBiologySpinal cordSurgeryPathology

Abstract

fetched live from OpenAlex

Enterovirus D68 (EV-D68) is an emerging picornavirus which causes severe respiratory disease, predominantly in children. In 2014, the largest and most widespread outbreak of EV-D68 described to date was reported in North America. Hospitals throughout the United States and Canada reported surges in patient volumes and resource utilization from August to October, 2014. In the US a total of 1,153 infections were confirmed in 49 states, although this is an underestimate of the likely millions of cases that occurred but were not tested. EV-D68 was detected in 14 patients who died; the role of the virus in these deaths is unknown. A possible association between EV-D68 and cases of acute flaccid paralysis with spinal cord gray matter lesions, known as acute flaccid myelitis, was observed during the outbreak and is under investigation. The 2014 outbreak of EV-D68 in North America demonstrates the public health importance of this emerging pathogen.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.080
GPT teacher head0.437
Teacher spread0.357 · 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
GenreReview

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

Citations113
Published2015
Admission routes1
Has abstractyes

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