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Record W4200489137 · doi:10.1093/jas/skab235.015

18 Genetic and Phenotypic Parameters for Aleutian Disease Tests and Their Correlations with Pelt Quality, Reproductive Performance, Packed-cell Volume, and Harvest Length in Mink

2021· article· en· W4200489137 on OpenAlexaff
Guoyu Hu, Duy Ngoc, Karim Karimi, Younes Miar

Bibliographic record

VenueJournal of Animal Science · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Virus Infections Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMinkBiologyGenetic correlationCullingVeterinary medicineAnimal scienceGenetic variationGeneticsMedicineGeneEcology

Abstract

fetched live from OpenAlex

Abstract Aleutian disease (AD) is an untreatable immune complex disease in mink and brings tremendous economic losses to the mink industry globally. The ineffectiveness of culling, immunoprophylaxis, and medical treatment in controlling AD have urged mink farmers to select AD-resilient mink based on the AD tests. However, the genetic analysis of these tests and their correlations with AD-resilient traits have not been investigated. In this study, data on 5,824 mink were used to estimate the genetic and phenotypic parameters of four AD tests, including two systems of enzyme-linked immunosorbent assay (ELISA), counterimmunoelectrophoresis (CIEP), and iodine agglutination test (IAT), and their genetic and phenotypic correlations with pelt quality, reproductive performance, packed-cell volume (PCV), and harvest length (HL). Significance (P < 0.05) of fixed effects (sex, year, color type, the number of mating, and dam age), covariates (age at blood sampling and age at harvest), and random effects (additive genetic, permanent environmental, and maternal effects) were determined using univariate models. The genetic and phenotypic parameters for all traits were estimated under bivariate models using ASReml 4.1. Estimated heritabilities (±SE) were 0.39±0.05, 0.61±0.07, 0.11±0.07, and 0.26±0.05 for antigen-based ELISA (ELISA-G), virus capsid protein-based ELISA, CIEP, and IAT, respectively. The ELISA-G showed moderate repeatability (0.58±0.04) and significant (P < 0.05) negative genetic correlations (±SE) with reproductive performance traits (from -0.41±0.16 to -0.49±0.12), PCV (-0.53±0.09), and HL (-0.45±0.16). These results indicated that the selection of mink with a lower ELISA-G score could not only decrease the anti-AMDV antibody level and the extent of anemia but also improve the female reproductive performance and the harvest length of mink without causing adverse influences on the pelt quality. Hence, ELISA-G could be applied as an indicator for genetic selection of AD-resilient mink and help mink farmers reduce the adverse effects of AD.

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 score0.074
Threshold uncertainty score0.336

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 studies0.0000.001
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 head0.040
GPT teacher head0.262
Teacher spread0.222 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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