MétaCan
Menu
Back to cohort
Record W2995445887

Effect of WUR Genotype on Resilience to a Multi-factorial Natural Disease Challenge in Pigs

2019· article· en· W2995445887 on OpenAlexaff
Jack C. M. Dekkers, Austin M. Putz, John C. S. Harding, Graham Plastow, Ryan L Jeon, Michael K. Dyck, Frédéric Fortin

Bibliographic record

VenueIowa State University animal industry report · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsCentre de Développement du Porc du QuébecUniversity of AlbertaUniversity of Saskatchewan
Fundersnot available
KeywordsGenotypeBiologyDiseaseAlleleResilience (materials science)GeneVirologyGeneticsVeterinary medicineBiotechnologyMedicineInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

The objectives of this study were to evaluate the effect of WUR genotype on disease resilience in pigs. Phenotypic data from 2,133 wean to finish pigs were collected in a natural disease challenge trial and associated with genotype at the WUR gene, which has previously been found to be associated with resistance to PRRS. The results from this study suggest that pigs that carry the favorable allele at this genetic marker have higher resilience to this multi-factorial natural disease challenge, which included the PRRS virus. PRRS plays an influential role in the swine industry, yet vaccinations have limited effectiveness due to the virus’ ability to mutate into new forms. Thus, leveraging genetics to develop more resilient commercial swine populations can not only mitigate the financial effects of various infectious diseases, but also increase the overall welfare of commercial swine.

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 score0.082
Threshold uncertainty score0.340

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 head0.023
GPT teacher head0.252
Teacher spread0.229 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueIowa State University animal industry reportSame topicAnimal Virus Infections StudiesFrench-language works237,207