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Record W3032585119 · doi:10.3389/fvets.2020.00275

Computed Tomographic Measures of Funnel-Shaped Lumbar Vertebral Canal and Articular Process Dysplasia Malformations Differ Between German Shepherd and Belgian Malinois Military Working Dogs

2020· article· en· W3032585119 on OpenAlexaboutno aff
Constance J. Dragicevich, Jeryl C. Jones, William C. Bridges, Heather Dunn

Bibliographic record

VenueFrontiers in Veterinary Science · 2020
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsnot available
FundersNational Institute of General Medical SciencesNational Institutes of HealthClemson University
KeywordsMedicineLumbarForamenHip dysplasiaLumbosacral jointLumbar vertebraeAnatomyDysplasiaRadiologyRadiographyPathology

Abstract

fetched live from OpenAlex

Researchers who study the selection and breeding program criteria for military working dogs aim to help maximize the years of active duty service. Computed tomographic (CT) quantitative phenotyping has been previously described as a method for supporting these research studies. Funnel-shaped lumbar vertebral foramen malformations have been previously described in Labrador retriever military working dogs and proposed to be risk factors for impaired arterial perfusion of nerve tissues during exercise. Articular process dysplasia malformations have been previously described in varying dog breeds and proposed to be risk factors for articular process degenerative joint disease and vertebral foramen stenosis. Aims of this retrospective, cross-sectional study were to describe quantitative CT phenotyping methods for characterizing funnel-shaped lumbar vertebral foramina and articular process dysplasia malformations and to apply these methods in a comparison between groups of German shepherd and Belgian Malinois military working dogs. A military working dog hospital’s database was searched for German shepherd and Belgian Malinois dogs aged < 6 years that had CT scans of the lumbosacral region during the period of 2008-2016. Observers unaware of CT findings recorded available clinical data for each of the dogs. An observer unaware of clinical data recorded CT measures of funnel-shaped lumbar vertebral foramina and articular process dysplasia malformations for each of dogs and each of the lumbar vertebrae that were available in the scans. A total of 59 dogs were sampled: 41 German shepherd and 18 Belgian Malinois. Articular process dysplasia and funnel-shaped vertebral foramen phenotypic traits were present in both breeds in this sample, with the frequency and quantitative measure of these traits being greater in German shepherd dogs and heavier dogs. Lower weight dogs had a lesser degree of a funnel-shaped foramen at all sampled vertebral locations. A consistent relationship between articular process dysplasia measures and body weight was not seen. Computed tomography measures of funnel shaped vertebral foramina were greater in German shepherd versus Belgian Malinois dogs at the L7 vertebra (P<0.01). The CT measures of cranial articular process dysplasia were greater in German shepherd versus Belgian Malinois dogs at the L4 (P<0.01) and L5 (P<0.05) vertebrae.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.059
GPT teacher head0.290
Teacher spread0.231 · 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 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

Citations2
Published2020
Admission routes1
Has abstractyes

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