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Record W2789980876 · doi:10.19103/as.2017.0013.14

Diseases affecting pigs: an overview of common bacterial, viral and parasitic pathogens of pigs

2018· book-chapter· en· W2789980876 on OpenAlexaboutno aff
Alejandro Ramirez

Bibliographic record

VenueBurleigh Dodds series in agricultural science · 2018
Typebook-chapter
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsOutbreakPandemicBiologyVirologyCoronavirus disease 2019 (COVID-19)MedicineDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Recent events such as the 2009 pandemic influenza outbreak, the continuous spread of African swine fever virus in Eastern Europe and the introduction of several new pathogens into the United States and their spread to Canada, Mexico, Central and South America have emphasized the ability of pig diseases to cross borders rapidly and the importance of global cooperation to improve the health and welfare of pigs. This chapter summarizes recent research on the causes and epidemiology of major bacteria, viruses and parasites found in pig production, focusing on those with a particular impact on safety and global production.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.906
Threshold uncertainty score0.865

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
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 head0.051
GPT teacher head0.282
Teacher spread0.230 · 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

Citations6
Published2018
Admission routes1
Has abstractyes

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