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Record W2906951132 · doi:10.3201/eid2502.180299

<i>Echinococcus multilocularis</i>Infection, Southern Ontario, Canada

2019· article· en· W2906951132 on OpenAlexafffundabout
Jonathon D. Kotwa, Mats Isaksson, Claire M. Jardine, G. Douglas Campbell, Olaf Berke, David L. Pearl, Nicola J. Mercer, Eva Osterman‐Lind, Andrew S. Peregrine

Bibliographic record

VenueEmerging infectious diseases · 2019
Typearticle
Languageen
FieldMedicine
TopicParasitic infections in humans and animals
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaBayer Animal HealthMinistry of Natural ResourcesCanadian Wildlife Health CooperativeWellcome TrustNational Center for Veterinary ParasitologyOntario Ministry of Natural Resources and Forestry
KeywordsEchinococcus multilocularisAlveolar echinococcosisVeterinary medicineEchinococcosisBiologyFecesPopulationCestodaEchinococcusZoologyHelminthsMedicineEcologyEnvironmental health

Abstract

fetched live from OpenAlex

Alveolar echinococcosis, the disease caused by infection with the intermediate stage of the Echinococcus multilocularis tapeworm, is typically fatal in humans and dogs when left untreated. Since 2012, alveolar echinococcosis has been diagnosed in 5 dogs, 3 lemurs, and 1 chipmunk in southern Ontario, Canada, a region previously considered free of these tapeworms. Because of human and animal health concerns, we estimated prevalence of infection in wild canids across southern Ontario. During 2015-2017, we collected fecal samples from 460 wild canids (416 coyotes, 44 foxes) during postmortem examination and analyzed them by using a semiautomated magnetic capture probe DNA extraction and real-time PCR method for E. multilocularis DNA. Surprisingly, 23% (95% CI 20%-27%) of samples tested positive. By using a spatial scan test, we identified an infection cluster (relative risk 2.26; p = 0.002) in the western-central region of the province. The cluster encompasses areas of dense human population, suggesting zoonotic transmission.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.006
GPT teacher head0.238
Teacher spread0.232 · 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 teacher head, not a consensus.

Study designObservational
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

Citations60
Published2019
Admission routes3
Has abstractyes

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