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Record W2045581902 · doi:10.3168/jds.2007-0608

A Meta-Analysis of the Impact of Monensin in Lactating Dairy Cattle. Part 2. Production Effects

2008· review· en· W2045581902 on OpenAlexaff
T.F. Duffield, A.R. Rabiee, I.J. Lean

Bibliographic record

VenueJournal of Dairy Science · 2008
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Guelph
FundersElanco Animal Health
KeywordsMonensinConjugated linoleic acidLinoleic acidAnimal scienceChemistryDairy cattleDry matterLactoseFood scienceLactationFatty acidBiologyBiochemistry

Abstract

fetched live from OpenAlex

A meta-analysis of the impact of monensin on production outcomes in dairy cattle was conducted using the 36 papers and 77 trials that contained eligible data. Statistical analyses were conducted in STATA and included a consideration of fixed or random effects models, assessment of publication bias, and impact of influential studies. Meta-regression was used to investigate sources of heterogeneity of response. There were 71 trials containing data from 255 trial sites and 9,677 cows examining milk production and composition. Monensin use in lactating dairy cattle significantly decreased dry matter intake by 0.3 kg, but increased milk yield by 0.7 kg and improved milk production efficiency by 2.5%. Monensin decreased milk fat percentage 0.13%, but had no effect on milk fat yield; however, there was significant heterogeneity between studies for both of these responses. Milk protein percentage was decreased 0.03%, but protein yield was increased 0.016 kg/d with treatment. Monensin had no effect on milk lactose percentage. Monensin increased body condition score by 0.03 and similarly improved body weight change (0.06 kg/d). Analysis of milk fatty acid profile data indicated that monensin was associated with a reduction of short-chain fatty acids (from 1 to 12% reduction) and stearic acid (-7.8%). The impact of monensin on linoleic and linolenic acids was variable, but monensin significantly increased conjugated linoleic acid (22%). Meta-regression of the effect of monensin on milk component percentages and yields indicated an influence of delivery method, stage of lactation, dose, and diet. Increasing concentrations of C18:1 in the diet enhanced the effect of monensin on decreasing milk fat yield, whereas increasing the rumen peptide balance increased the effect of monensin on milk protein yield. These findings indicate a benefit of monensin for improving milk production efficiency while maintaining body condition. The effect of monensin on milk fat percentage and yield was influenced by diet.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.832
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0000.005
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.124
GPT teacher head0.343
Teacher spread0.219 · 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 designOther design
Domainnot available
GenreReview

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

Citations175
Published2008
Admission routes1
Has abstractyes

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