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Genetic Analysis of Reproductive Traits and Antibody Response in PRRS Infected Sows

2014· report· en· W42386488 on OpenAlexafffund
Nick V. L. Serão, Oswald Matika, Steve Bishop, B. Kemp, John C. S. Harding, Graham Plastow, Jack C. M. Dekkers

Bibliographic record

Venuenot available
Typereport
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsUniversity of AlbertaUniversity of Saskatchewan
FundersGenome CanadaCanadian Swine Health Board
KeywordsBiologyHerdTraitOutbreakAntibody responseGenetic correlationPorcine reproductive and respiratory syndrome virusAntibodyHeritabilityVirologyGeneticsZoologyVirusGenetic variationGeneAnimal science

Abstract

fetched live from OpenAlex

The genetic components of reproductive performance and antibody response of 641 commercial sows were assessed in a commercial herd that faced a PRRS outbreak. Antibody response after the PRRS outbreak was highly heritable and had high genetic correlations with reproductive traits. Many genomic regions were associated with antibody response in this study. These results indicate that there is a significant genomic component associated with PRRS antibody response and its high genetic correlations with reproductive traits during PRRS suggest that this trait could be used as an indicator trait to reduce the impact of PRRS on reproductive performance.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.038
GPT teacher head0.303
Teacher spread0.265 · 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 designBench or experimental
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
Published2014
Admission routes2
Has abstractyes

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