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Characterization of Dairy Production Systems in Countries that Participate in the International Bull Evaluation Service

2001· article· en· W2053092411 on OpenAlexaboutno aff
N.R. Zwald, K.A. Weigel, W.F. Fikse, Romdhane Rekaya

Bibliographic record

VenueJournal of Dairy Science · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEffects of Environmental Stressors on Livestock
Canadian institutionsnot available
Fundersnot available
KeywordsHerdIce calvingSireLactationGeographyCzechAnimal scienceYield (engineering)Agricultural scienceBiologyPregnancy

Abstract

fetched live from OpenAlex

The International Bull Evaluation Service Centre has routinely calculated international dairy sire evaluations since 1994. Production systems vary between countries and between herds within a country, and these differences can cause significant genotype x environment interactions. First-lactation records of Holstein cows calving from January 1, 1990 through December 31, 1997, were used in this study. Countries that provided data for this study included Australia, Austria, Belgium, Canada, Czech Republic, Estonia, Finland, Germany, Hungary, Ireland, Israel, Italy, The Netherlands, New Zealand, South Africa, Switzerland, and the United States. Country means were calculated for 13 variables related to climate, herd management, and genetic background. These variables were considered as possible causes of genotype by environment interaction. Highest peak yields were found in Israel and the United States at 31.4 and 30.5 kg, respectively. New Zealand and Estonia had the lowest daily peak yields at 17.1 and 18.9 kg, respectively. This was consistent with genetic differences between these countries, because Israel had the highest average predicted transmitting abilities (PTA) milk among sires, while Estonia had the lowest PTA milk. Persistency of lactation, defined as milk yield at 240 d postpartum divided by milk yield at 60 d postpartum, was highest in the Czech Republic and Estonia at 1.34, and lowest in Israel at 1.05. Herd size also varied substantially between countries, ranging from 2.3 first-lactation cows per herd-year in Finland to 62 per herd-year in Hungary. In summary, tremendous variation exists between the leading dairy countries in management, genetic, and climatic factors.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score0.101

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.041
GPT teacher head0.268
Teacher spread0.228 · 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

Citations27
Published2001
Admission routes1
Has abstractyes

Explore more

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