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Record W2003333808 · doi:10.7589/0090-3558-39.3.675

IMMOBILIZATION OF NORTH AMERICAN PORCUPINES (ERETHIZON DORSATUM) USING KETAMINE AND XYLAZINE

2003· article· en· W2003333808 on OpenAlexaff
Pat Morin, Dominique Berteaux

Bibliographic record

VenueJournal of Wildlife Diseases · 2003
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Pharmacology and Anesthesia
Canadian institutionsMcGill UniversityUniversité du Québec à Rimouski
Fundersnot available
KeywordsXylazineKetamine hydrochloridePorcupineKetamineAnesthesiaRespirationBiologyAnimal scienceMedicineAnatomy

Abstract

fetched live from OpenAlex

We performed 345 immobilizations on 150 North American porcupines (Erethizon dorsatum) using a mixture of ketamine hydrochloride (KH) and xylazine hydrochloride (XH). A subsample of 184 immobilizations performed on 124 individuals from 4 May to 7 November 2000 and from 22 January to 30 April 2001 is thoroughly analyzed. In contrast to published procedures, we found that injecting drugs into tail muscles was more efficient than into longitudinal muscles of the lower back, because tail injections decreased the need of multiple injections by 26%. Using tail injections, we were able to reduce the dose by 50% from other published reports without significantly affecting induction, immobilization, standing, or recovery times. We suggest that injection of 5 mg KH/kg and 2 mg XH/kg in the tail as a standard procedure to immobilize North American porcupines. Body mass significantly affected the induction and standing times for single injections performed in the tail, irrespective of dose or sex. Sex, dose, and mass had no effect on the quality of immobilizations and the respiration rate of individuals during immobilization. We report a 0.87% mortality rate using a mixture of KH and XH and suggest ways to further decrease this rate.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.529

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.042
GPT teacher head0.329
Teacher spread0.287 · 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

Citations17
Published2003
Admission routes1
Has abstractyes

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