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Record W203970008

Reduction in pain response by combined use of local lidocaine anesthesia and systemic ketoprofen in dairy calves dehorned by heat cauterization.

2010· article· en· W203970008 on OpenAlexaff
T.F. Duffield, Anneliese Heinrich, Suzanne T. Millman, Andrew DeHaan, Shelley James, K. Lissemore

Bibliographic record

VenuePubMed · 2010
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Pharmacology and Anesthesia
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsKetoprofenMedicineAnesthesiaLidocaineCauterizationSalineSurgery
DOInot available

Abstract

fetched live from OpenAlex

This study assessed the efficacy of ketoprofen for mitigating pain following dehorning with an electric cautery iron. Forty Holstein heifer calves, 4 to 8 wk of age, were randomized to receive a lidocaine cornual nerve block and either an injection of ketoprofen (3 mg/kg IM) or physiological saline, 10 min prior to dehorning. Cortisol was measured from serum obtained 10 min prior to dehorning and at 3 and 6 h post-dehorning. Calf behavior was video-recorded between 0 to 2, 3 to 5, and 6 to 8 h post-dehorning, and frequency of ear flicks, head shakes, head rubs, lying, standing, feeding, and grooming were recorded. Finally, 24-h intake of calf starter was recorded. There was no effect of treatment on cortisol (P > 0.1); however, ketoprofen-treated calves displayed less ear-flicks and total head behavior (P < 0.05), and tended to consume more starter (P = 0.09) than control calves. Ketoprofen is effective for mitigating behavioral effects of postsurgical pain following dehorning in 4- to 8-week-old calves.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.033
GPT teacher head0.263
Teacher spread0.230 · 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 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

Citations45
Published2010
Admission routes1
Has abstractyes

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