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Ultrasonographic Adrenal Gland Measurements in Healthy Yorkshire Terriers and Labrador Retrievers

2012· article· en· W2158663302 on OpenAlexaboutno aff
Thibault de Chalus, Anaïs Combes, Anne‐Sophie Bedu, Pascaline Pey, Sylvie Daminet, Luc Duchateau, Jimmy Saunders

Bibliographic record

VenueAnatomia Histologia Embryologia · 2012
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Medicine and Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsLabrador RetrieverAdrenal glandMedicineAnatomyPopulationLongitudinal studyPathology

Abstract

fetched live from OpenAlex

An upper threshold of 7.4 mm for maximal adrenal gland diameter is commonly used to detect pituitary-dependent hyperadrenocorticism ultrasonographically in dogs. There is a substantial overlap between adrenal gland diameter of healthy dogs and of those with pituitary-dependent hyperadrenocorticism. The aim of this study is to determine the measurements of both adrenal glands, in particular, of the height at the caudal glandular pole in a longitudinal plane, in the Labrador retriever and Yorkshire terrier, two breeds widely represented in the population suspected of hyperadrenocorticism. Seventeen Labrador retrievers and 24 Yorkshire terriers considered healthy were included in the study. Adrenal gland measurements were taken on static images and comprised in measurements of the length in a longitudinal plane (L), of the height at the cranial (CrHLG) and caudal pole (CdHLG) in a longitudinal plane and in a transverse plane (CrHTR and CdHTR, respectively), and of the width at the cranial and caudal poles in a transverse plane (CrWTR and CdWTR, respectively). This study established new upper thresholds for the left and right height at the caudal pole measured in a longitudinal plane: 7.9 mm (left) and 9.5 mm (right) for the Labrador retrievers and 5.4 mm (left) and 6.7 mm (right) for the Yorkshire terriers. All the measurements were significantly different between the two breeds. There was a significant relationship between CdHTR and CdHLG, and the age of the dogs for both breeds.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.089
GPT teacher head0.323
Teacher spread0.234 · 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.

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

Citations29
Published2012
Admission routes1
Has abstractyes

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