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Record W1953492154 · doi:10.1111/evj.12295

Infection control and biosecurity in equine disease control

2014· review· en· W1953492154 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEquine Veterinary Journal · 2014
Typereview
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBiosecurityOutbreakInfection controlDiseaseInfectious disease (medical specialty)Disease controlPopulationMedicineVeterinary medicineIntensive care medicineEnvironmental healthVirologyPathology

Abstract

fetched live from OpenAlex

Infectious diseases are an important cause of morbidity and mortality in horses, along with economic costs and broader impacts associated with the loss of members of a species that generates income, acts as a working animal and is a companion. Endemic diseases continue to challenge, emerging diseases are an ever-present threat and outbreaks can be both destructive and disruptive. While infectious diseases can never be completely prevented, measures can be introduced to restrict the entry of pathogens into a population or limit the implications of the presence of a pathogen. Objective research regarding infection control and biosecurity in horses is limited, yet a variety of practical infection prevention and control measures can be used. Unfortunately, infection control can be challenging, because of the nature of the equine industry (e.g. frequent horse movement) and endemic pathogens, but also because of lack of understanding or motivation to try to improve practices. Recognition of the basic concepts of infection control and biosecurity, and indeed the need for measures to control infectious diseases, is the foundation for successful infection prevention and control.

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.

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)0.000
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 score0.971
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.027
GPT teacher head0.316
Teacher spread0.289 · 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