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Record W4317399089 · doi:10.1080/19336896.2023.2166749

Sheep scrapie and deer rabies in England prior to 1800

2023· article· en· W4317399089 on OpenAlexafffund
Anthony Ness, Judd M. Aiken, Debbie McKenzie

Bibliographic record

VenuePrion · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPrion Diseases and Protein Misfolding
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsScrapieOutbreakBovine spongiform encephalopathyRabiesVirologyDiseaseBiologyVeterinary medicineZoologyMedicinePrion proteinPathology

Abstract

fetched live from OpenAlex

Eighteenth-century England witnessed the emergence of two neurological diseases in animals. Scrapie, a transmissible spongiform encephalopathy, is a fatal neurodegenerative disease of sheep and goats that appears in classical and atypical forms. Reports of classical scrapie in continental Europe with described symptoms date back to 1750 in what is now western Poland. However, two major outbreaks of scrapie appeared in England prior to the 1800s. References to a sheep disease with a resemblance to scrapie first appear in Southwestern England between 1693 and 1722 and in the East Midlands between 1693 and 1706. Concurrent with the descriptions of scrapie in sheep was a neurological disease of deer first appearing in the East of England. Two 18th-century writers remarked on the symptomatic similarities between the sheep and deer neurological diseases. Multiple outbreaks of the unknown deer disease existing as early as 1772 are examined and are identified as rabies.

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)0.001
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 score0.053
Threshold uncertainty score0.105

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.258
Teacher spread0.248 · 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

Citations10
Published2023
Admission routes2
Has abstractyes

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