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Record W2809140893 · doi:10.3354/dao03262

Toxoplasma gondii infection in stranded St. Lawrence Estuary beluga Delphinapterus leucas in Quebec, Canada

2018· article· en· W2809140893 on OpenAlexaffabout
Asma Iqbal, Lena N. Measures, Stéphane Lair, Brent R. Dixon

Bibliographic record

VenueDiseases of Aquatic Organisms · 2018
Typearticle
Languageen
FieldImmunology and Microbiology
TopicToxoplasma gondii Research Studies
Canadian institutionsHealth Canada
Fundersnot available
KeywordsBelugaBeluga WhaleBiologyToxoplasma gondiiZoologyEstuaryPopulationFisheryEcologyEnvironmental healthMedicineImmunology

Abstract

fetched live from OpenAlex

The St. Lawrence Estuary (SLE) beluga Delphinapterus leucas in Quebec, Canada, is endangered due to intensive hunting in the 19th and 20th centuries and subsequent anthropogenic contamination and human activities in the region. Infectious disease is a primary cause of death in this population. The protozoan parasite Toxoplasma gondii is reported in numerous marine mammal species, including beluga. In the present study, 55 tissue samples (heart and brain) collected from 34 stranded SLE beluga were analysed by PCR followed by DNA sequencing and restriction fragment length polymorphism analysis (RFLP) to determine the PCR prevalence and genotypes of T. gondii in these beluga. Of 34 beluga tested, 44% were positive for T. gondii by PCR, with males having a higher prevalence of infection than females and with more infected neonates and juveniles than adults. Molecular analyses indicated that all T. gondii infecting stranded SLE beluga grouped into genotype II, which predominates in humans. While our results indicate that a high prevalence of stranded beluga are PCR-positive for T. gondii infection, very few deaths are attributed to toxoplasmosis based on published necropsy results. Toxoplasma gondii can cause a range of diseases, including neurological deficits, and more data are needed to investigate this parasite's effect on population recovery.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.164
Threshold uncertainty score0.925

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.010
GPT teacher head0.245
Teacher spread0.236 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations20
Published2018
Admission routes2
Has abstractyes

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