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Hepatitis E virus and neurological disorders

2017· review· en· W2627136785 on OpenAlexaff
Brendan McLean, James Gulliver, Harry R. Dalton

Bibliographic record

VenuePractical Neurology · 2017
Typereview
Languageen
FieldMedicine
TopicHepatitis Viruses Studies and Epidemiology
Canadian institutionsRoyal Ottawa Mental Health Centre
Fundersnot available
KeywordsMedicinePolyradiculoneuropathyAsymptomaticMeningoencephalitisAcute hepatitisGuillain-Barre syndromeHepatitisHepatitis C virusDiseasePediatricsImmunologyVirusPathology

Abstract

fetched live from OpenAlex

Hepatitis E is the most common cause of hepatitis worldwide. While originally considered a disease of developing countries, it is increasingly recognised in developed countries, probably related to contaminated pork meat, and where infection is often asymptomatic. However, several non-liver manifestations have become apparent, the most important of which are neurological, including Guillain-Barré syndrome (acute inflammatory demyelinating polyradiculoneuropathy (AIDP)), neuralgic amyotrophy and meningoencephalitis. We recommend testing all patients with AIDP and neuralgic amyotrophy for hepatitis E and consider testing any patient with an unexplained neurological illness and abnormal liver function tests for the virus.

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)0.000
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.252
GPT teacher head0.476
Teacher spread0.224 · 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

Citations47
Published2017
Admission routes1
Has abstractyes

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