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Record W3114394361 · doi:10.1017/s1466252320000237

Unleashing the literature: a scoping review of canine zoonotic and vectorborne disease research in <i>Canis familiaris</i> in North America

2020· review· en· W3114394361 on OpenAlexaff
Danielle Julien, Jan M. Sargeant, Catherine Filejski, Ali Versluis, Victoria Waind, Sherilee L. Harper

Bibliographic record

VenueAnimal Health Research Reviews · 2020
Typereview
Languageen
FieldMedicine
TopicZoonotic diseases and public health
Canadian institutionsPublic Health OntarioMinistry of Health and Long Term CareUniversity of AlbertaUniversity of Guelph
Fundersnot available
KeywordsRabiesCanisEhrlichia canisZoonotic diseaseVeterinary medicineMedicineVirologyGeographyDiseaseEnvironmental healthBiologyImmunologySerologyPathology

Abstract

fetched live from OpenAlex

Domestic dogs (Canis familiaris) provide important benefits to human beings but can also transmit pathogens. Information on the breadth of canine zoonoses and vectorborne research in North America is scarce. A scoping review was conducted to examine (1) the number and type of canine zoonoses and vectorborne studies in domestic dogs conducted in North America since the start of the 21st century; (2) the main research methods reported; (3) the Inequality-adjusted Human Development Index (IHDI) countries in which research was conducted; and (4) whether collaborative integrated terminology was reported in objectives or methods sections. Title/abstract screening, full-text screening, and data-charting were completed by two reviewers. We identified 507 publications evaluating 43 zoonotic or vectorborne pathogens in domestic dogs. Most studies (n = 391 of 512 (76.37%)) were conducted in the USA. The five most frequently researched pathogens were Ehrlichia spp. (n = 81 of 507 (15.98%)), Borrelia burgdorferi (n = 64 of 507 (12.62%)), Leptospira spp. (n = 54 of 507 (10.65%)), Rabies virus (n = 42 of 507 (8.28%)), and Influenza viruses (n = 41 of 507 (8.09%)). These pathogens can cause moderate to severe health outcomes in human beings and in dogs irrespective of IHDI ranking; our review highlights important counts of research conduct among North American countries.

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)0.023
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.507
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0230.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0010.012
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.006
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 head0.371
GPT teacher head0.548
Teacher spread0.177 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations5
Published2020
Admission routes1
Has abstractyes

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