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Record W1998717049 · doi:10.3168/jds.2010-3243

Estimation of genetic parameters for measures of calf survival in a population of Holstein heifer calves from a heifer-raising facility in New York State

2010· article· en· W1998717049 on OpenAlexafffundabout
L. Henderson, F. Miglior, A. Sewalem, D.F. Kelton, A. Robinson, K.E. Leslie

Bibliographic record

VenueJournal of Dairy Science · 2010
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaHolstein Association USAU.S. Department of Agriculture
KeywordsSireCullingIce calvingHerdWeaningAnimal sciencePopulationBiologySurvival analysisDemographyStatisticsLactationMathematicsPregnancyGenetics

Abstract

fetched live from OpenAlex

The objectives of this study were to estimate the genetic parameters of survival to weaning and survival to exit for a population of Holstein calves from New York State, as well as to associate the estimated breeding values determined in the current study with traits from ongoing genetic evaluations used in Canada and the United States. Data were recorded for 7,372 heifer calves at a commercial rearing facility in New York State from arrival at 1 to 7 d of age for the duration of stay at the facility (on average, heifers departed the facility 1 mo before calving). Performance and disease up to weaning and mortality before and after weaning were recorded. Analyzed data were limited to daughters of sires with at least 10 calves originating from farms that had sent a minimum of 5 calves to be raised at the facility. As such, calves from 264 sires and 36 herds were studied using 2 statistical methods. The first method, calf survival, used a Weibull proportional hazards model, with survival defined as age at culling, death, or censoring. The second method, a 2-trait sire model, included survival from arrival to weaning (SUV1) and survival from weaning to exit (SUV2). Both models included fixed effects of arrival weight, serum total protein, weaning weight, season and year of birth, and calving ease score. Herd and sire were included as random effects. Significant associations among all fixed effects and calf survival were observed. In general, very light or heavy weight at arrival, low total protein, low weaning weight, and difficult birth increased risk of mortality for calves. The heritability of survival from the first method was 0.063. The heritabilities from the linear model were 0.001 for SUV1 and 0.036 for SUV2. The genetic correlation between SUV1 and SUV2 was 0.58. Genetic variance was close to zero for survival of calves to weaning, but was greater for survival after weaning through the growing period. Breeding values were estimated for SUV1 and SUV2 and correlated with routinely evaluated traits from Canadian and US genetic evaluations. Significant associations between genetic evaluations for survival traits and routinely evaluated traits in Canada and the United States were found, in particular with conformation body traits, somatic cell score, fertility, and longevity.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.067
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.144
GPT teacher head0.368
Teacher spread0.224 · 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

Citations34
Published2010
Admission routes3
Has abstractyes

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