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Record W780174597 · doi:10.21423/aabppro20074604

Meta-analysis of the Metabolic Impacts of Monensin in Lactating Dairy Cattle

2007· article· en· W780174597 on OpenAlexaffabout
T.F. Duffield, A.R. Rabiee, I.J. Lean

Bibliographic record

VenueAmerican Association of Bovine Practitioners Conference Proceedings · 2007
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicRuminant Nutrition and Digestive Physiology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMonensinRumenPropionateButyrateDairy cattleNEFAPopulationBeef cattleAnimal scienceFatty acidBiologyChemistryFood scienceBiochemistryMedicineFermentationEnvironmental health

Abstract

fetched live from OpenAlex

Monensin shifts the microbial population in the rumen towards more gram negative bacteria, consequently changing rumen volatile fatty acid concentrations towards propionate and away from acetate and butyrate. Since the late 1980's there have been many papers published on the effects of monensin in lactating dairy cattle. Recently, approvals for use on monensin have been obtained in Canada and the United States, while the product has been available for dairy cattle in countries such as Mexico, Australia and New Zealand for many years. The impacts of monensin on energy metabolism, including effects on serum ketones, NEFA, glucose, and urea have not always been consistent. Meta-analysis is a useful tool that can be employed to both summarize effects across studies and to investigate factors explaining potential heterogeneity of response.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.532
Threshold uncertainty score0.424

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
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 head0.038
GPT teacher head0.278
Teacher spread0.240 · 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 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

Citations0
Published2007
Admission routes2
Has abstractyes

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