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Record W2754652265

Powassan Virus and Other Tick-Borne Pathogens from Wildlife and Companion Animals in Southern Ontario

2017· dissertation· en· W2754652265 on OpenAlexfundaboutno aff
Kathryn A. Smith

Bibliographic record

VenueThe Atrium (University of Guelph) · 2017
Typedissertation
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Wildlife Health CooperativeOntario Ministry of Natural Resources and ForestryMinistry of Natural Resources
KeywordsWildlifeBiologyGeographyTickTick-borne diseaseVirologyVeterinary medicineEcologyMedicine
DOInot available

Abstract

fetched live from OpenAlex

The objectives of the present research were to survey potential vertebrate host and tick species for evidence of infections with POWV and other arthropod-borne pathogens including West Nile virus, Heartland virus, Anaplasma phagocytophilum, Babesia microti, Borrelia miyamotoi, B. burgdorferi and Ehrlichia chaffeensis in mammalian wildlife, dogs and ticks in southern Ontario. During the summers of 2015-2016, ticks and tissues were collected from carcasses of free-ranging, medium-sized mammals; blood and ticks were collected from live-trapped mammals, and ticks removed from dogs were collected from local veterinary clinics. Albeit rarely, evidence of the presence of POWV was found both by polymerase chain reaction in ticks and serological tests in groundhogs (Marmota monax) and striped skunks (Mephitis mephitis). Evidence of A. phagocytophilum and B. burgdorferi was also rarely detected in Ixodes scapularis ticks. These findings emphasize the importance of both broad and targeted surveillance strategies for investigating emerging tick-borne diseases.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.083
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
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 head0.024
GPT teacher head0.248
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 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

Citations0
Published2017
Admission routes2
Has abstractyes

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