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Record W2129405738 · doi:10.3415/vcot-14-09-0144

Radiographic and computed tomographic assessment of the development of the antebrachia and elbow joints in Labrador Retrievers with and without medial coronoid disease

2015· article· en· W2129405738 on OpenAlexaboutno aff
H.A.W. Hazewinkel, George Voorhout, Seng Fong Lau

Bibliographic record

VenueVeterinary and Comparative Orthopaedics and Traumatology · 2015
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineElbowComputed tomographicRadiographyAnatomyOrthodonticsRadiologyComputed tomography

Abstract

fetched live from OpenAlex

OBJECTIVES: To compare the development, monitored by radiography and computed tomography, of the antebrachia and elbow joints in seven Labrador Retrievers with healthy elbow joints and in seven Labrador Retrievers that developed medial coronoid disease (MCD), in order to determine whether disturbances in the development of the antebrachia and elbow joints, between the age of six and 17 weeks may lead to medial coronoid disease. METHODS: A prospective study of 14 Labrador Retrievers in their active growth stage was performed. The development of the antebrachia and elbow joints was assessed between six and 17 weeks of age using radiography and computed tomography determining the development of secondary ossification centres, radioulnar length ratio, radial angulation, and inter-relationship between the humerus, ulna and radius. RESULTS: For the parameters of ossification of secondary ossification centres, radioulnar length ratio, radial angulation, and joint congruence evaluation, there was no significant difference in the development of the antebrachia and elbow joints of seven Labrador Retrievers positive and seven Labrador Retrievers negative for MCD at the age of six to 17 weeks. CLINICAL SIGNIFICANCE: These findings demonstrate that the development of MCD in the Labrador Retrievers in our study was not related to any disturbance in the development of the antebrachia and elbow joints during the rapid growth phase.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004
Threshold uncertainty score0.734

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.096
GPT teacher head0.321
Teacher spread0.225 · 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

Citations16
Published2015
Admission routes1
Has abstractyes

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