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Record W2131024693 · doi:10.2174/1874331501105010063

Crossbreeding Results in Canadian Dairy Cattle for Production, Reproduction and Conformation

2011· article· en· W2131024693 on OpenAlexafffundabout
L.R. Schaeffer, Edward B. Burnside, Paige Glover, J. Fatehi

Bibliographic record

VenueThe Open Agriculture Journal · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsUniversity of Guelph
FundersAgriculture and Agri-Food Canada
KeywordsPurebredCrossbreedIce calvingMilkingAnimal scienceBiologyBreedSireHerdReproductionBrown SwissHeterosisVeterinary medicineLactationAgronomyPregnancyGeneticsMedicine

Abstract

fetched live from OpenAlex

Progeny of Holstein females mated to sires of different breeds were genetically evaluated along with their purebred Holstein contemporaries born in the same herds using multiple trait animal models. The resulting estimated breeding values (EBV) of cows were averaged within breed of sire and compared relative to progeny of purebred Holstein sires for various economic traits. All progeny were born since 2005, and only animals from herds with crossbreds were included in the genetic evaluation models. Crossbred cows were significantly below Holstein sired cows for 305-d EBV for milk yield, but were above Holsteins for fat and protein yields. There were no significant differences between crossbreds and purebreds for somatic cell scores. Crossbred cows and heifers became pregnant sooner after each calving, had higher non-return rates, fewer services, and shorter gestation lengths than purebred Holsteins. Crossbred heifers and cows had lower stillbirth rates due to having smaller calves, and slightly better calving ease. Objectively measured conformation traits (seven) and milking speed and milking temperament were analyzed by multiple trait models. Differences for conformation favoured Holsteins over crossbreds. There were no significant differences for milking speed or temperament between crossbreds and purebreds.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.729
Threshold uncertainty score0.985

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.028
GPT teacher head0.254
Teacher spread0.226 · 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 designNot applicable
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
Published2011
Admission routes3
Has abstractyes

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