MétaCan
Menu
Back to cohort
Record W4414501743 · doi:10.1111/vru.70092

Shape and Variability of the Normal Medial Coronoid Process by Computed Tomography in Young Adult Labrador Retrievers

2025· article· en· W4414501743 on OpenAlexaboutno aff
L. van der Laan, Robert M. Kirberger, Geoffrey T. Fosgate, C. Roux

Bibliographic record

VenueVeterinary Radiology & Ultrasound · 2025
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsnot available
Fundersnot available
KeywordsCoronoid processHounsfield scaleElbowComputed tomographySuperimpositionLameness

Abstract

fetched live from OpenAlex

Medial coronoid process disease (MCPD) is the most frequently observed cause of elbow dysplasia, resulting in lameness in young, fast-growing large-breed dogs, including Labrador Retrievers (LRs). Computed tomography (CT) is the diagnostic imaging modality of choice for evaluating the medial coronoid process (MCP), as it is noninvasive and eliminates superimposition of the process by the radial head. This retrospective descriptive study aimed to describe the shape of the normal MCP on CT, to assess its variability within the LR breed, and to determine the normal Hounsfield units (HUs) of the MCP, medial radial head (MRH), and lateral radial head (LRH). Normal elbow CT studies of 51 South African guide dog LRs were reviewed. Using a repeatable imaging alignment technique, three principal MCP shapes were identified: ovoid, triangular, and softly pointed and were found to be dependent on the level of assessment. Males had significantly lower mean MCP HU compared to females. The mean HU of the MRH was consistently higher than the LRH and was also greater in attenuation on subjective assessment. Measuring MCP and radial head HU too proximally was suboptimal, as volume averaging was frequently encountered. The results of this study showed that although different alignment techniques may result in HU variations, they will not affect the HU to such an extent that the MCP would be misclassified as abnormal.

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)0.000
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 score0.188
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.012
GPT teacher head0.268
Teacher spread0.256 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueVeterinary Radiology & UltrasoundSame topicVeterinary Orthopedics and NeurologyFrench-language works237,207