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Record W2481084717

Plasma concentrations of buprenorphine following a single subcutaneous administration of a sustained release formulation of buprenorphine in sheep.

2016· article· en· W2481084717 on OpenAlexaff
Chiara Zullian, Pablo Lema, Mélissa Lavoie, Aurore Dodelet-Devillers, Francis Beaudry, Pascal Vachon

Bibliographic record

VenuePubMed · 2016
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Pharmacology and Anesthesia
Canadian institutionsCegep de Saint Hyacinthe
Fundersnot available
KeywordsBuprenorphinePlasma concentrationSubcutaneous injectionAnalgesicAnimal scienceMedicineBody weightChemistryAnesthesiaInternal medicineBiologyOpioid
DOInot available

Abstract

fetched live from OpenAlex

The goal of the present study was to evaluate the potential use of slow release buprenorphine in sheep. Twelve adult female sheep (6 Dorset and 6 Suffolk, 12 months of age) were used for this project and were divided into 2 experimental groups (n = 6/group comprising 3 Dorset and 3 Suffolk sheep). Sustained release (SR) buprenorphine was administered subcutaneously in the scapular region at a concentration of 0.1 mg/kg body weight (BW) for group 1 and of 0.05 mg/kg BW for group 2. Following blood collections at selected time points, plasma concentrations of buprenorphine was performed by tandem liquid chromatograph-mass spectrometry. Mean buprenorphine concentration was above 0.1 ng/mL at 48 h up to 192 h post-injection for group 1 and it was above 0.1 ng/mL at 48 h up to 72 h post-injection for group 2. In conclusion, a long lasting potential analgesic plasma level of buprenorphine is attained following a single subcutaneous injection of 0.1 mg/kg BW of SR buprenorphine in sheep. However the effective analgesic plasma threshold still needs to be determined in sheep.

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 score0.002

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 head0.040
GPT teacher head0.279
Teacher spread0.239 · 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

Citations9
Published2016
Admission routes1
Has abstractyes

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