MétaCan
Menu
Back to cohort
Record W2801960011 · doi:10.1093/envhis/emy010

The Great Epizootic of 1872–73: Networks of Animal Disease in North American Urban Environments

2018· article· en· W2801960011 on OpenAlexfundaboutno aff
Sean Kheraj

Bibliographic record

VenueEnvironmental History · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicYersinia bacterium, plague, ectoparasites research
Canadian institutionsnot available
FundersYork University
KeywordsEpizooticOutbreakUrbanizationGeographyCentralityEpidemic diseaseInfectious disease (medical specialty)DiseaseEcologyBiologyVirologyMedicine

Abstract

fetched live from OpenAlex

This article examines the outbreak of an unknown illness (later thought to be equine influenza) among the horses of Toronto and its subsequent spread as a continent-wide panzootic. Known as the Great Epizootic, the illness infected horses in nearly every major urban center in Canada and the United States over a 50-week period beginning in late September 1872. The Great Epizootic not only illustrated the centrality of horses to the functioning of nineteenth-century North American cities, but it also demonstrated that these cities generated ecological conditions and a networked disease pool capable of supporting the rapid spread of animal disease on a continental scale in localities from widely divergent geographies. This article invites environmental historians to broaden their view of cities to consider the ways in which networked urbanization produced forms of historical biotic homogenization that could result in the rapid and widespread outbreak of disease.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.257

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.006
GPT teacher head0.210
Teacher spread0.204 · 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

Citations9
Published2018
Admission routes2
Has abstractyes

Explore more

Same venueEnvironmental HistorySame topicYersinia bacterium, plague, ectoparasites researchFrench-language works237,207