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Record W2753817673 · doi:10.1002/jmv.24933

Non‐polio <i>Enterovirus</i> detection with acute flaccid paralysis: A systematic review

2017· review· en· W2753817673 on OpenAlexaff
Sneha Suresh, Sarah Forgie, Joan Robinson

Bibliographic record

VenueJournal of Medical Virology · 2017
Typereview
Languageen
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsStollery Children's HospitalUniversity of Alberta
Fundersnot available
KeywordsEnterovirusEchovirusSerotypePoliomyelitisAcute flaccid paralysisVirologyPoliovirusMedicineEnterovirus InfectionsVirus

Abstract

fetched live from OpenAlex

Acute flaccid paralysis (AFP), as defined by the World Health Organization (WHO), is characterized by an acute onset of limb weakness. In the post-polio era, other enterovirus (EV) serotypes associated with AFP may become more prominent. This study aims to collate the data on the non-polio enteroviruses (NPEV) associated with AFP. A systematic review of published case reports, case series, and surveillance studies of AFP from 1960 through 2017 was undertaken. Data were collected including the country of the study, number of specimens positive for NPEV and available clinical data. The majority of studies originated from Asia. In surveillance studies, EV 71 (a serotype of Enterovirus A) was the most commonly detected serotype with AFP, followed by Enterovirus B serotype echovirus 11 and then Enterovirus B serotype echovirus 11. In case studies and case reports, EV 71 and EV 68 (a serotype of Enterovirus D), were the most commonly detected NPEV. As poliovirus eradication continues, there is a need to ensure that AFP surveillance will also detect other potentially vaccine preventable viruses.

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)0.003
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.017
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.004
Bibliometrics0.0080.008
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.438
Teacher spread0.373 · 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 designSystematic review
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

Citations85
Published2017
Admission routes1
Has abstractyes

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