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Record W3138871905 · doi:10.1177/1098612x211001042

Serologic and urinary survey of exposure to <i>Leptospira</i> species in a feral cat population of Prince Edward Island, Canada

2021· article· en· W3138871905 on OpenAlexaffabout

Bibliographic record

VenueJournal of Feline Medicine and Surgery · 2021
Typearticle
Languageen
FieldImmunology and Microbiology
TopicLeptospirosis research and findings
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsLeptospirosisSerologyTransmission (telecommunications)PopulationCATSFeral cat

Abstract

fetched live from OpenAlex

Objectives Recent studies show that cats could play an important role in the transmission of Leptospira species. There are few reports of leptospirosis on Prince Edward Island (PEI) and none in cats. The objective of this study was to determine the prevalence of serum antibodies against Leptospira serovars and of Leptospira DNA in the urine of a population of free-roaming cats. Methods Paired blood and urine samples were collected from 200 cats brought to a trap–neuter–return program. Antibody titers against six Leptospira serovars (Bratislava, Canicola, Gryppotyphosa, Hardjo, Pomona, Icterohaemorrhagiae) were determined by microscopic agglutination test. PCR was performed on urine samples to identify urine shedding of Leptospira DNA. Results Antibodies were detected in 20/200 cats (10%) for at least one serovar, with titers ranging from 1:50 to 1:6400 (all serovars tested, except Hardjo). Urine samples of 7/200 cats (3.5%) were PCR-positive. Conclusions and relevance Feral cats in PEI had a higher than expected exposure to leptospirosis and can shed DNA from pathogenic Leptospira species in urine. Further studies are needed to determine the prevalence of exposure to leptospirosis in other species on PEI and the potential role of feral cats in transmission of the disease.

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)0.001
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 score0.075
Threshold uncertainty score0.951

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.030
GPT teacher head0.264
Teacher spread0.234 · 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
Published2021
Admission routes2
Has abstractyes

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