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Record W1972702362 · doi:10.1586/14787210.2014.892827

Parasitic diseases in travelers: a focus on therapy

2014· review· en· W1972702362 on OpenAlexafffund
Adrienne Showler, Mary Wilson, Kevin C. Kain, Andrea K. Boggild

Bibliographic record

VenueExpert Review of Anti-infective Therapy · 2014
Typereview
Languageen
FieldImmunology and Microbiology
TopicParasites and Host Interactions
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsExpert opinionIntensive care medicineMedicineParasitic diseaseParasitic infectionImmunologyDiseasePathology

Abstract

fetched live from OpenAlex

Parasitic infections are an important cause of illness among returned travelers, and can lead to considerable morbidity and, in some cases, mortality. The complexity of parasitic life cycles and geographic specificities can present diagnostic challenges, particularly in non-endemic settings to which most travelers return for care. Clinical manifestations reflect the diverse taxonomy and pathogenesis of parasites, and appropriate diagnosis and management therefore necessitate a high index of suspicion of parasitic illnesses. Much of our knowledge surrounding management of parasitic infections in travelers is extrapolated from evidence derived in endemic populations, or is based on expert opinion and case series. We herein provide an overview of parasitic diseases of short-term travelers, and summarize current therapeutic strategies for each illness.

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.038
GPT teacher head0.400
Teacher spread0.362 · 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

Citations10
Published2014
Admission routes2
Has abstractyes

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