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Record W4416319931 · doi:10.1590/0103-8478cr20250008

Use of the semi-quantitative test with terbutaline sulfate for the identification of anhidrosis in Quarter Horses used in vaquejada events

2025· article· pt· W4416319931 on OpenAlexaboutno aff
Gabriela Carvalho Calafange Costa de Medeiros, Ubiratan Pereira de Melo, Cíntia Ferreira

Bibliographic record

VenueCiência Rural · 2025
Typearticle
Languagept
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsnot available
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsAnhidrosisSWEATSerial dilutionSweat testSalineQuarter (Canadian coin)

Abstract

fetched live from OpenAlex

ABSTRACT: Anhidrosis, characterized by the partial or total reduction in sweat production, is a relevant condition in equines living in tropical climates, particularly those engaged in physical activity. This study evaluated the prevalence of anhidrosis in Quarter Horses used in the vaquejada sport, utilizing the semi-quantitative sweat test with terbutaline sulfate. Sixty Quarter Horses of both sexes, actively competing, were included in the study. The experimental procedure involved the intradermal application of a saline control solution and seven serial dilutions of terbutaline sulfate, ranging from 100 mg/L to 10-6 mg/L, at predefined points in the cervical region. After solution application, the injection sites were assessed over a minimum of 20 minutes to observe the response to the test. The analysis criterion was based on the intensity of sweating at each concentration, enabling the classification of animals as healthy, partially anhidrotic, or completely anhidrotic. The study revealed a significant prevalence (75%) of partial anhidrosis among Quarter Horses. The results underscore the importance of accurate diagnosis of partial anhidrosis to understand its impact on equine health and performance.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.285
Threshold uncertainty score0.720

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.084
GPT teacher head0.376
Teacher spread0.292 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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