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Record W3163171086

Anesthesia techniques used for field castration of 10 intractable horses.

2021· article· en· W3163171086 on OpenAlexaff
Bruce C Stover, Nigel Caulkett

Bibliographic record

VenuePubMed · 2021
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Pharmacology and Anesthesia
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSedationMedicineCastrationOrchiectomyAnesthesiaHorseMargin (machine learning)SurgeryComputer scienceInternal medicineBiology
DOInot available

Abstract

fetched live from OpenAlex

Dealing with an intractable horse is a reality for nearly every equine or mixed animal veterinarian. Establishing an adequate level of sedation prior to induction of anesthesia for various clinical procedures involves little margin for error regarding the safety of the veterinarian, handler, and patient. This is further compounded by the extreme difficulty of gaining venous access required to obtain rapid and reliable results. This case series describes a technique of intramuscular sedation used for field castration of 10 captive, formerly wild horses, which may be useful for various other types of intractable horses. Key clinical message: An alternative method to sedate intractable horses for induction of anesthesia is outlined. The techniques described are accessible for most veterinary practitioners, providing small-volume, fast, and reliable intramuscular sedation.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.069
GPT teacher head0.324
Teacher spread0.254 · 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 designCase report
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

Citations1
Published2021
Admission routes1
Has abstractyes

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