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Record W2093409609 · doi:10.1100/2012/863024

Distribution of<i>BoLA-DRB3</i>Allelic Frequencies and Identification of Two New Alleles in Iranian Buffalo Breed

2012· article· en· W2093409609 on OpenAlexaff
Jafar Mosafer, Mahyar Heydarpour, E. Manshad, George C. Russell, Г. Е. Сулимова

Bibliographic record

VenueThe Scientific World JOURNAL · 2012
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsMcMaster UniversityPopulation Health Research Institute
Fundersnot available
KeywordsAlleleBreedGeneticsBiologyLocus (genetics)Major histocompatibility complexAllele frequencyGene

Abstract

fetched live from OpenAlex

The role of the major histocompatibility complex (MHC) in the immune response makes it an attractive candidate gene for associations with disease resistance and susceptibility. This study describes genetic variability in the BoLA-DRB3 in Iranian buffaloes. Heminested PCR-RFLP method was used to identify the frequency of BoLA-DRB3 alleles. The BoLA-DRB3 locus is highly polymorphic in the study herd (12 alleles). Almost 63.50% of the alleles were accounted for by four alleles (BoLA-DRB3.2 ∗48, ∗20, ∗21, and obe) in Iranian buffalo. The DRB3.2 ∗48 allele frequency (24.20%) was higher than the others. The frequencies of the DRB3.2 ∗20 and DRB3.2 ∗21 are 14.52 and 14.00, respectively, and obe and gbb have a new pattern. Significant distinctions have been found between Iranian buffalo and other cattle breed studied. In the Iranian buffaloes studied alleles associated with resistance to various diseases are found.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.025
GPT teacher head0.287
Teacher spread0.262 · 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 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

Citations8
Published2012
Admission routes1
Has abstractyes

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Same venueThe Scientific World JOURNALSame topicMicrobial infections and disease researchFrench-language works237,207