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Record W4403046941 · doi:10.3389/fvets.2024.1455468

Canine epilepsy/seizure occurrence in primary care and referral populations: a look into the epidemiology across countries

2024· review· en· W4403046941 on OpenAlexaff
Meaghan E. Bride, Francesca Samarani, Lauren E. Grant, Fiona James

Bibliographic record

VenueFrontiers in Veterinary Science · 2024
Typereview
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsEpidemiologyEpilepsyReferralContext (archaeology)Socioeconomic statusPrimary careMedicinePopulationFamily medicineIndigenousEnvironmental healthPsychiatryGeographyPathology

Abstract

fetched live from OpenAlex

Epilepsy is a common neurological condition in dogs. Analysis of primary care populations across countries can provide a more complete understanding of the epidemiology of this condition and provide context for spectrum of care discussions. This narrative literature review was aimed at understanding canine epilepsy/seizure prevalence in primary care populations, and changes in occurrence across geography, culture, and socioeconomic status. There are few studies to give insight into the true general population of epileptic canines and there is inconsistency in the literature regarding the standards applied for epilepsy diagnosis across primary care and referral practices. Therefore, the future focus should be on more epidemiological research in primary care and mixed populations, more veterinary education to standardize use of medical guidelines in primary care settings, and increased awareness of the benefits of having pet insurance to mitigate the potentially substantial cost of care for dogs with epilepsy.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.939
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.002
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.127
GPT teacher head0.447
Teacher spread0.320 · 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 designNot applicable
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

Citations6
Published2024
Admission routes1
Has abstractyes

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