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Record W3024115458

A One Health approach to rabies management in Manitoba, Canada.

2019· article· en· W3024115458 on OpenAlexaffabout
Shauna Richards, Richard Rusk, Dale Douma

Bibliographic record

VenuePubMed · 2019
Typearticle
Languageen
FieldImmunology and Microbiology
TopicRabies epidemiology and control
Canadian institutionsUniversity of ManitobaAgriculture Food and Rural DevelopmentManitoba Health
Fundersnot available
KeywordsRabiesDomestic animalAnimal healthRage (emotion)GeographyVeterinary medicineMedicineBiologyVirology
DOInot available

Abstract

fetched live from OpenAlex

A One Health approach was developed in the province of Manitoba in 2014 to manage human and domestic animal exposures to rabies. Manitoba Rabies Central is a collaboration of 3 provincial departments responsible for animal, human, and environmental health. Since the inception of the program 537 samples from animals suspected of rabies and causing an exposure to a human or domestic animal have been evaluated with 11.3% testing positive, 85.7% testing negative, and 3.0% being unfit for testing. Most of the positive rabies test results came from skunks (52.0%), which accounted for 12.5% of submissions. Dogs and cats accounted for 52.5% of submissions; however, only 18.9% of these animals tested positive for rabies. Domestic animals were more likely to be exposed to a rabid animal (most commonly skunks) than were humans. Humans were more likely to be exposed to dogs and cats (regardless of rabies test result).

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.637

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.002
Scholarly communication0.0020.000
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.026
GPT teacher head0.202
Teacher spread0.176 · 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

Citations3
Published2019
Admission routes2
Has abstractyes

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