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Evaluation of Net Energy Expenditures of Dairy Cows According to Body Weight Changes over a Full Lactation

2006· article· en· W2069859439 on OpenAlexafffund
J.L. Ellis, F. Qiao, J.P. Cant

Bibliographic record

VenueJournal of Dairy Science · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Food and AgricultureCargill
KeywordsLactationNet energyAnimal scienceBody weightMilk fatDairy cattleBiologyFood scienceEndocrinologyPregnancy

Abstract

fetched live from OpenAlex

Equations that predict daily dry matter intake (DMI) of a lactating cow could be evaluated by comparing the predicted accumulation of energy in body weight (BW) over the course of lactation with the observed BW evolution. However, to do so requires that first the energy balance calculations from observed DMI are evaluated. The purpose of the work reported here was to determine the degree of deviation of predicted from observed BW, according to net energy for lactation (NE(L)) balance calculated from weekly observations of DMI, BW, and fat-corrected milk production in 21 sets of full-lactation data, and to determine an appropriate correction of the NE(L) bias for subsequent DMI prediction evaluations. When the National Research Council maintenance equation 0.08 x BW(kg)(0.75) was used in energy balance calculation, BW was overpredicted with an increasing difference between the cumulative predicted BW and observed BW as lactation progressed. Placing all the error of BW prediction into maintenance energy expenditures resulted in a best-fit equation of 0.096 +/- 0.003 Mcal/kg of BW(0.75). A time-dependent equation was also developed, in which weekly maintenance expenditures were determined as the NE(L) expenditure to yield a zero NE(L) balance and could be described by a second-order polynomial equation related to week of lactation (WOL) where maintenance NE(L) = [-0.0227(+/- 0.0098) x WOL2 + 1.352(+/- 0.456) x WOL + 78.09(+/- 4.92) Mcal/kg of BW(0.75)] x 10(-3). Average maintenance energy expenditure at the onset of lactation was approximately 0.08 Mcal/kg of BW(0.75), and this value increased to a plateau at wk 15 of lactation of approximately 0.098 Mcal/kg of BW(0.75). Standard deviations between data sets of weekly maintenance parameter estimates throughout lactation were large but consistent at approximately 25% of the mean. Revision of the maintenance energy expenditure estimate substantially improved BW prediction by the energy balance model. On average, the 0.096 Mcal of NE(L)/kg of BW(0.75) equation resulted in the best BW predictions, although substantial variation existed around this value.

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)0.002
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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.016
GPT teacher head0.283
Teacher spread0.266 · 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

Citations23
Published2006
Admission routes2
Has abstractyes

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