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Record W4307708949 · doi:10.3168/jdsc.2022-0231

Effect of partial exchange of lactose with fat in milk replacer on performance and blood metabolites of Holstein calves

2022· article· en· W4307708949 on OpenAlexafffund
J. Echeverry-Munera, L. Amado, H. Berends, L.N. Leal, M.A. Steele, J. Martín‐Tereso

Bibliographic record

VenueJDS Communications · 2022
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaAlberta MilkUniversity of Guelph
KeywordsLactoseNEFAStarterWeaningAnimal scienceRandomized block designBody weightCarbohydrateChemistryBiologyFood scienceEndocrinologyMedicineInternal medicineInsulin

Abstract

fetched live from OpenAlex

The objective of this study was to determine the effect of dietary energy source (fat vs. carbohydrate) in calf milk replacer (MR) on growth performance parameters and feed intake in rearing calves. In a randomized complete block design, 68 Holstein calves [40 females and 28 males; (mean ± SD) body weight (BW): 43.7 ± 1.43 kg] were assigned to 17 blocks of 4 calves based on birth date and parity of the dam. Within each block, calves were randomly assigned to 1 of 2 treatments: a high-lactose MR (HL; 17% fat; 44% lactose; n = 34), or a high-fat MR (HF; 23% fat; 37% lactose; n = 34). Lactose was exchanged for fat on a weight per weight basis, resulting in a 6% difference in metabolizable energy density per kilogram of MR. The feeding plan started with 6 L/d for 7 d, then 8 L/d for 35 d, 6 L/d for 7 d, and finally, 4 L/d for 7 d. Milk replacer allowances were offered in 2 meals per day at 140 g/L. Measurements included daily MR, starter and straw intakes, weekly BW, and blood metabolites, including nonesterified fatty acids (NEFA) and glucose, on wk 4, 6, 8, and 10. Increasing fat at the expense of lactose did not affect MR intake or solid feed intake during the preweaning and weaning periods. However, HF calves tended to consume more solid feed than HL calves during the postweaning period (2.63 ± 0.08 vs. 2.52 ± 0.08 kg/d). Additionally, average daily gain (HF = 0.78 ± 0.02, HL = 0.77 ± 0.02 kg/d) and final BW (HF = 98.8 ± 1.53, HL = 97.7 ± 1.57 kg) were not affected by MR composition. Nevertheless, NEFA concentration was higher in HF calves than in HL calves (0.21 ± 0.01 vs. 0.17 ± 0.01 mmol/L), and glucose concentration was higher in HF calves (6.52 ± 0.23 vs. 5.86 ± 0.23 mmol/L). Under the conditions of this study, HF calves consumed similar amounts of solid feed and grew comparably to the HL calves; however, the isonitrogenous replacement of lactose by fat had evident metabolic effects, such as increased blood NEFA and glucose concentrations.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.046
GPT teacher head0.341
Teacher spread0.295 · 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

Citations6
Published2022
Admission routes2
Has abstractyes

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