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Record W4387048325 · doi:10.1111/jvp.13409

Depletion of dexamethasone in cattle: Food safety study in dairy and beef cattle

2023· article· en· W4387048325 on OpenAlexafffundabout
Al Chicoine, D.L. Renaud, Saad Enouri, Patricia M. Dowling, Yu Gu, Ron J. Johnson

Bibliographic record

VenueJournal of Veterinary Pharmacology and Therapeutics · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPharmacological Effects and Assays
Canadian institutionsUniversity of GuelphUniversity of Saskatchewan
FundersOntario Ministry of Agriculture, Food and Rural AffairsDairy Farmers of OntarioBeef Farmers of Ontario
KeywordsDexamethasoneRegimenBeef cattleWithdrawal timeDairy cattleAnimal scienceMedicineBiologyInternal medicine

Abstract

fetched live from OpenAlex

Dexamethasone is approved for cattle in Canada for several conditions, but no withdrawal times are currently provided on the approved labels. Recently, the list of Maximum Residues Limits for Veterinary Drugs in Foods in Canada was amended to include dexamethasone. The objectives of this study were to determine the residue depletion profile of dexamethasone after an extra-label dosage regimen in milk of healthy lactating dairy cattle (n = 18) and in edible tissues of healthy beef cattle (n = 16) and to suggest withdrawal intervals. Dexamethasone was administered intramuscularly at 0.05 mg/kg daily for 3 days. Milk samples were collected prior to treatment and every 12 h up to 96 h post-dose. Muscle, liver, kidney, and peri-renal fat tissues were collected from beef cattle at 3, 7, 11, or 15 days post-dose. Dexamethasone analysis was performed by liquid chromatography/mass spectrophotometry. Dexamethasone residues were detected in milk samples up to 36 h. Muscle and fat had no detectable dexamethasone residues while kidney and liver had detectable residues only on day 3 post-dose. A withdrawal interval of 48 h for milk in Canadian dairy cattle and 7 days for meat in Canadian beef cattle are suggested for the dexamethasone treatment regimen most commonly requested to CgFARAD™.

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)0.000
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 score0.792
Threshold uncertainty score0.184

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.072
GPT teacher head0.342
Teacher spread0.271 · 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
Published2023
Admission routes3
Has abstractyes

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