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Record W2944697948 · doi:10.1111/tbed.13220

Dynamic contact networks of swine movement in Manitoba, Canada: Characterization and implications for infectious disease spread

2019· article· en· W2944697948 on OpenAlexafffundabout
Carolyn Augusta, Graham W. Taylor, Rob Deardon

Bibliographic record

VenueTransboundary and Emerging Diseases · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsVector InstituteUniversity of CalgaryUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsTruckGeographyConstruct (python library)Infectious disease (medical specialty)DiseaseComputer scienceMedicineEngineering

Abstract

fetched live from OpenAlex

We use swine shipping data from Manitoba to construct one-mode dynamic contact networks of swine locations and two-mode location-to-truck networks at four time scales: daily, weekly, monthly and for the entire two-year study period. We provide measures of graph evolution and graph characterization for each, useful in the development of statistical models related to infectious disease transmission. We find that Manitoba shipping practices differ from those in other Canadian regions, and particularly that truck sharing is more common in Manitoba than elsewhere in the country.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.132
Threshold uncertainty score0.983

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.214
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 teacher head, 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

Citations8
Published2019
Admission routes3
Has abstractyes

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