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Selection Indices in Holstein Cattle of Various Countries

2005· article· en· W2028778461 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Dairy Science · 2005
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsAgriculture and Agri-Food Canada
Fundersnot available
KeywordsSelection (genetic algorithm)Index (typography)Production (economics)ReproductionStatisticsBiologyBiotechnologyMathematicsEconomicsEcologyComputer science

Abstract

fetched live from OpenAlex

Fifteen countries, based on geographical representation, Interbull membership, and size of progeny testing programs, provided a brief description of national selection index and top bull listings from August 2003. Individual traits included in each selection index were grouped into 3 components as they related to production, durability, and health and reproduction. The relative emphasis for each component within the selection index, as well as the number of common bulls among top listings were compared across countries. Average relative emphasis for production, durability, and health and reproduction, across all countries, was 59.5, 28, and 12.5%, respectively. The main difference between selection indices in various countries was the relative emphasis on production. Overall, the Danish S-Index had the most balanced emphasis across the 3 components, with 34% on production, 29% on durability, and 37% on health and reproduction. Broadening of breeding goals through recent changes to selection indices decreased the similarities of top bull listings across the various countries, with a slightly greater commonality among sires of top bulls.

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.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.469
Threshold uncertainty score0.165

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 head0.007
GPT teacher head0.251
Teacher spread0.243 · 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