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Record W2113110586 · doi:10.1139/z2012-046

Effects of different doses of medetomidine and tiletamine–zolazepam on the duration of induction and immobilization in free-ranging yearling brown bears (<i>Ursus arctos</i>)

2012· article· en· W2113110586 on OpenAlexaffvenue
Johanna Painer, Andreas Zedrosser, Jon M. Arnemo, Åsa Fahlman, Sven Brunberg, Peter Segerström, Jon E. Swenson

Bibliographic record

VenueCanadian Journal of Zoology · 2012
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Pharmacology and Anesthesia
Canadian institutionsUniversity of Calgary
FundersNaturvårdsverket
KeywordsMedetomidineUrsusBiologyAnesthesiaAnestheticMedicineEndocrinologyPopulationHeart rate

Abstract

fetched live from OpenAlex

We compared anesthetic protocols with different doses of tiletamine–zolazepam (TZ) combined with medetomidine (M) for 288 yearling brown bear ( Ursus arctos L., 1758) immobilizations with the objective of finding a combination of doses that would provide fast induction with a duration of anesthesia long enough to minimize the need for administering additional drug. The duration of induction time and immobilization was dose-dependent. Increasing the M dose resulted in significantly shorter induction times and a lower probability of giving supplemental drugs. Increasing the TZ dose prolonged duration of anesthesia. For yearling brown bears in Scandinavia, captured shortly after den emergence in April and May, we recommend total dart doses of 1.0–1.66 mg M/dart, plus 62.5–125 mg TZ/dart, depending on the individual requirements for the length and depth of anaesthesia.

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)0.001
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
Metaresearch0.0000.001
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 integrity0.0000.001
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 head0.026
GPT teacher head0.263
Teacher spread0.237 · 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

Citations6
Published2012
Admission routes2
Has abstractyes

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