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Record W4409112822 · doi:10.1111/vru.70027

Imaging Diagnosis—Sonographic Features of Bilateral Renal Lymphangiectasia in an Azotemic Dog

2025· article· en· W4409112822 on OpenAlexaboutno aff
Yu Wang, Wilfried Maï, Lisa H. Dourmashkin, Victoria Leopardi, Hayley Amerman

Bibliographic record

VenueVeterinary Radiology & Ultrasound · 2025
Typearticle
Languageen
FieldMedicine
TopicVascular Malformations and Hemangiomas
Canadian institutionsnot available
FundersNational Institutes of Health
KeywordsMedicineLymphangiectasiaAzotemiaHistopathologyRadiologyPathologyLymphatic systemInternal medicineRenal function

Abstract

fetched live from OpenAlex

A 9-year-old male neutered Labrador Retriever was referred for azotemia and bilateral renomegaly. An abdominal ultrasound revealed severe bilateral renomegaly with septated subcapsular cystic anechoic lesions, consistent with renal lymphangiectasia. Despite conservative management, the patient died. Necropsy and histopathology confirmed dilated subcapsular vascular structures. Renal lymphangiectasia is a rare, benign dilation of renal lymphatics previously reported in human medicine. This case represents the first description of sonographic features of renal lymphangiectasia in a canine patient.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.300
Teacher spread0.287 · 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 designCase report
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

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