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Record W2145654768 · doi:10.1017/s1014233900001590

Genetic base and inbreeding of Canadienne, Brown Swiss, Holstein and Jersey cattle in Canada

2003· article· en· W2145654768 on OpenAlexaffabout
C. Hansen, J.N.B. Shrestha, R. J. Parker, G. H. Crow, James N. Derr

Bibliographic record

VenueAnimal Genetic Resources Information · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsUniversity of ManitobaAgriculture and Agri-Food Canada
Fundersnot available
KeywordsInbreedingPedigree chartBrown SwissBreedBiologyPopulationAnimal scienceDairy cattleEffective population sizeArtificial inseminationBeef cattleHerdDemographyBiotechnologyGenetic diversityGenetics

Abstract

fetched live from OpenAlex

Summary The narrowing of the genetic base is of major concern to many cattle breeders and this is a consequence of a small effective population size and an increase in the inbreeding coefficient in cattle populations. Studies of pedigrees of cattle populations found in Canada showed that the effective population size and rate of inbreeding over a 12-year period (1983–94) were 123 and 0.412 percent for Canadienne, 975 and 0.054 percent for Brown Swiss, and 2 183 and 0.024 percent for Jersey cattle populations. Over the same period, the year to year trends in inbreeding coefficients based on co-ancestry was 0.11 percent for Canadienne and 0.07 percent for Brown Swiss cattle populations, and 0.37 percent for Holstein bulls used by the artificial insemination industry. Inbreeding was not found to be a major problem in any of the populations examined. However, only 10 bulls of their respective breed sired 61 percent of the Canadienne, 21 percent of the Brown Swiss, and 29 percent of the Jersey cattle populations, and 41 percent of the Holstein bulls in the bull studs. More and more breeders are demanding proven sires to increase milk production from fewer cows resulting in the narrowing of the genetic base of the national cattle populations. Newer technology that provides precise genetic modification could further contribute to the narrowing of the genetic base compromising the ability to sustain current production and respond to changing markets in the long-term.

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 score0.199
Threshold uncertainty score0.755

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 head0.005
GPT teacher head0.175
Teacher spread0.169 · 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

Citations4
Published2003
Admission routes2
Has abstractyes

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