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Record W2119916993 · doi:10.3382/ps.2013-03475

The influence of genetic background versus commercial breeding programs on chicken immunocompetence

2014· article· en· W2119916993 on OpenAlexaff
Mehdi Emam, Hassan Mehrabani-Yeganeh, Neda Barjesteh, Gholamreza Nikbakht Brujeni, K.A. Thompson-Crispi, S Charkhkar, Bonnie A. Mallard

Bibliographic record

VenuePoultry Science · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsImmunocompetenceBiologyImmune systemImmunityAntigenImmunologyGenetic variationSelective breedingGeneticsGene

Abstract

fetched live from OpenAlex

Immunocompetence of livestock plays an important role in farm profitability because it directly affects health maintenance. Genetics significantly influences the immune system, and the genotypic structure of modern fast-growing chickens has been changed, particularly after decades of breeding for higher production. Therefore, this study was designed to help determine if intensive breeding programs have adversely affected immunocompetence or whether the immune response profiles are controlled to greater extent by genetic background. Thus, 3 indigenous chicken populations from different genetic backgrounds and 2 globally available modern broiler strains, Ross 308 and Cobb 500, were evaluated for various aspects of immune response. These included antibody responses against sheep red blood cells and Brucella abortus antigen, as well as some aspects of cell-mediated immunocompetence by toe web swelling test and in vitro blood mononuclear cell proliferation. Significant differences (P < 0.05) in antibody responses to both antigens and cellular proliferation were observed among populations but not consistently between modern commercial strains versus the indigenous populations. In fact, the immune response profiles of Cobb 500 were similar to the indigenous populations, but varied compared with the other commercial strain. In addition, considerable variation was recorded between indigenous populations for all responses measured in this study. The results of this study suggest that the variation observed in immune responses between these strains of chickens is most likely due to differences in the genetic background between each strain of chicken rather than by commercial selection programs for high 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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.953
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.034
GPT teacher head0.255
Teacher spread0.221 · 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

Citations22
Published2014
Admission routes1
Has abstractyes

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