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Record W2549786066 · doi:10.3168/jds.2016-11747

The effects of periparturient administration of flunixin meglumine on the health and production of dairy cattle

2016· article· en· W2549786066 on OpenAlexafffund
Nathalie C. Newby, K.E. Leslie, H.D.Putnam Dingwell, D.F. Kelton, Daniel M. Weary, L. Neuder, Suzanne T. Millman, T.F. Duffield

Bibliographic record

VenueJournal of Dairy Science · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsUniversity of British ColumbiaUniversity of Guelph
FundersMerck Animal HealthOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsRetained placentaIce calvingMetritisMedicinePlaceboAnimal scienceMilk productionDairy cattleVeterinary medicineLactationPregnancyBiologyPlacenta

Abstract

fetched live from OpenAlex

Research on the assessment and management of pain in cows following difficult or assisted calving is still limited, especially on the effects of analgesics intended to mitigate this pain. The purpose of this study was to assess the effects of flunixin meglumine on the health and production of Holstein cows after calving. In total, 34 flunixin-treated and 38 placebo-treated animals were enrolled in a precalving treatment trial. A total of 633 animals given flunixin and 632 animals administered a placebo were enrolled in a postcalving treatment trial. In both cases, animals were randomly assigned to treatment, and researchers were blind to treatment condition until after analysis. A total of 1,265 animal records were analyzed for milk production for the first 14d in milk and health outcomes for the first 30d in milk. Animals treated with flunixin meglumine before calving had a significantly increased risk of stillbirth. Animals treated immediately after calving had increased odds of having a retained placenta and, in turn, increased risk of a high temperature, decreased milk production, and an increased risk of developing metritis. The administration of flunixin meglumine within 24h of parturition is not recommended in dairy cattle.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.504
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.019
GPT teacher head0.263
Teacher spread0.244 · 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 designBench or experimental
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

Citations52
Published2016
Admission routes2
Has abstractyes

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