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Record W4242035265 · doi:10.4141/a06-asmgabstracts

Proceedings of the 2006 meeting of the Animal Science Modelling Group

2006· article· en· W4242035265 on OpenAlexaffvenue
J. France, E. Kebreab, Mary Beth Hall, N.R. St-Pierre, J. Dijkstra, A. Bannink, L.A. Crompton, Secundino López, P.A. Abrahamse, P. Chilibroste, John Mills, Raymond C. Boston, Peter J. Moate, Darko Stefanovski, A.G. Ríus, E.S. Kolver, C.C. Palliser

Bibliographic record

VenueCanadian Journal of Animal Science · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsGroup (periodic table)BiologyChemistry

Abstract

fetched live from OpenAlex

The supply of glucogenic nutrients may limit the production of milk on grass based diets.Glucogenic nutrients are necessary for lactose and fat synthesis (glycerol and NADPH requirements for milk fat).Current feed evaluation systems that assess the energy value of the diet and the energy requirements of the cow are based on metabolisable energy (ME) or net energy (NE).These systems hardly consider the characteristics of the energy delivering nutrients.Mechanistic models have been developed that take into account site of feed digestion, type of nutrient absorbed and type of nutrients required for production of milk constituents, and thus may overcome the limitations of empirical feed evaluation systems.The objective of this study is to compare energy or nutrient supply on grass based diets with the energy or nutrients required for observed milk production calculated from empirical energy systems and from a mechanistic model.The energy systems evaluated are the Dutch NE system, the AFRC ME system, and the Feed Into Milk (FIM) ME system.The mechanistic model is based on the models of Dijkstra et al. (1996) and Mills et al. (2001).A total of 41 treatments of grass-based diets from 11 experiments were used for evaluation.Assessment of the error of energy or nutrient supply relative to requirement was made by the mean square prediction error (MSPE) and concordance correlation coefficient (CCC).In the mechanistic model, the supply of glucogenic nutrients was always more limiting towards milk production than the supply of aminogenic nutrients or the supply of energy.The residual MSPE was lowest for the mechanistic model (6.1%), followed by the Dutch NE system (8.2%),FIM ME system (9.7%) and AFRC ME system (11.8%).In all models, the energy or nutrient supply exceeded the energy or nutrient requirement.CCC values were 0.21 (AFRC ME system), 0.31 (FIM ME system), 0.48 (Dutch NE system) and 0.61 (mechanistic model) and confirmed the higher accuracy and precision of the mechanistic model.In conclusion, current energy evaluation systems overestimate energy supply relative to energy requirement on grass-based diets for dairy cattle.The mechanistic model predicted glucogenic nutrients limit milk production and performed much better than the energy evaluation systems.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.068
Threshold uncertainty score0.226

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0680.022

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 head0.206
Teacher spread0.196 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2006
Admission routes2
Has abstractyes

Explore more

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