MétaCan
Menu
Back to cohort
Record W7065996009

Genetic variability of health disorders in Ontario Holstein cows

2008· dissertation· en· W7065996009 on OpenAlexaffabout

Bibliographic record

VenueeScholarship@McGill (McGill) · 2008
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsMcGill University
Fundersnot available
KeywordsHeritabilitySireSelection (genetic algorithm)HerdGenetic variabilityGenetic gainDairy cattleYield (engineering)
DOInot available

Abstract

fetched live from OpenAlex

Extensive emphasis on selection for milk yield with minimal attention to the animals' functional performance has increased the yield of North American dairy cattle. The high intensity of selection for production traits such as milk yield, protein yield and fat yield has also brought about a rapid increase in genetic relationships among animals. In dairy cattle, correlated response to selection for milk yield includes fertility and susceptibility to diseases. Although the high producing cows have greater net profit, they also have higher mammary and discarded milk costs associated with high production. Long-term genetic selection against clinically diagnosed diseases might be useful to diminish their incidence. The Scandinavian countries have incorporated the health traits into their selection indices. Canadian breeding programs realize the need to consider traits other than the yield in selection decisions. The objective of this study was to determine the genetic variability of various clinically diagnosed health traits. Data from 171 herds of the Ontario milk-recording program were used. These herds are collaborating with the University of Guelph (Dr. David Kelton) to record health traits. A major impediment to estimating heritabilities for the majority of the disorders was that the progeny group size per sire was not large enough to enable detecting a significant difference among sires. Hence, heritability estimates were not obtained for all the health disorders included in the study. The progeny group size per sire has to be increased such that there are at least 5 cases per progeny group to enable detecting a difference among sires. Heritability estimates for retained placenta and displaced abomasum in the first lactation were 0.067 and 0.212 respectively. The heritability estimate of cystic ovaries in the second lactation was 0.092. In the third lactation, the heritability estimate of mastitis was 0.10 whereas retained placenta had a heritability of 0.25.

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 score0.212
Threshold uncertainty score0.427

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
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 head0.010
GPT teacher head0.228
Teacher spread0.218 · 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

Citations0
Published2008
Admission routes2
Has abstractyes

Explore more

Same venueeScholarship@McGill (McGill)Same topicAtomic and Molecular PhysicsFrench-language works237,207