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Record W4412121381 · doi:10.1002/vrc2.70138

Renal lymphoma diagnosis via urinary cytology and PCR for antigen receptor rearrangement in a cat

2025· article· en· W4412121381 on OpenAlexaff
Katharine S. Woods, M. Casey Gaunt

Bibliographic record

VenueVeterinary Record Case Reports · 2025
Typearticle
Languageen
FieldMedicine
TopicVeterinary Oncology Research
Canadian institutionsVictoria HospitalUniversity of Prince Edward Island
Fundersnot available
KeywordsMedicineCytologyUrinary systemLymphomaPathologyAntigenInternal medicineImmunology

Abstract

fetched live from OpenAlex

Abstract A client‐owned 8‐year‐old male neutered Norwegian Forest cat presented with suspected neurological episodes. Cellular preservation was poor on a cytocentrifuged slide of a urine sample from cystocentesis; however, low‒moderate numbers of possible variably sized lymphocytes were observed, raising concern for lymphoma. Abdominal ultrasonography revealed marked bilateral nephropathy, hydronephrosis, and severe pyelectasia. Repeated microscopic urinalysis via cystocentesis identified numerous large lymphocytes containing magenta granules, which are supportive of large granular lymphocyte lymphoma. PCR for antigen receptor rearrangements using the urine sample revealed a clonally rearranged T‐cell receptor gene, which was consistent with T‐cell neoplasia. A chemotherapy protocol consisting of vincristine, cytarabine, doxorubicin, and prednisolone was initiated; however, the patient's condition deteriorated following administration of vincristine, prompting euthanasia. Necropsy was declined by the owner.

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)0.002
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.051
GPT teacher head0.363
Teacher spread0.312 · 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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