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Record W2777846547

Is enterovirus 71-vaccinatie ook nodig in Nederland?

2014· article· nl· W2777846547 on OpenAlexaff
Katja C. Wolthers, Menno D. de Jong

Bibliographic record

VenueData Archiving and Networked Services (DANS) · 2014
Typearticle
Languagenl
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsOutbreakMedicineEnterovirus 71ChinaVaccinationVirologyEnvironmental healthEnterovirusVirus
DOInot available

Abstract

fetched live from OpenAlex

Enterovirus 71 (EV71) is an emerging infection, causing large outbreaks in Asia with high morbidity and mortality in children. New vaccines against EV71 have been developed and tested in China, leading to two recent publications on the efficacy of these vaccines in The New England Journal of Medicine. Although the results look promising, it is not expected that vaccination against EV71 will be introduced in Europe any time soon. Large outbreaks with high morbidity have not yet been observed in Europe, and the genotypes causing these outbreaks in Asia circulate only to a low extent in Europe. However, in the future this might change, and experience with EV71 vaccination as is now gained in China might be valuable

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)0.002
metaresearch head score (Gemma)0.003
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: Empirical · Consensus signal: none
Teacher disagreement score0.030
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.029
GPT teacher head0.306
Teacher spread0.277 · 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
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

Citations0
Published2014
Admission routes1
Has abstractyes

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