MétaCan
Menu
Back to cohort
Record W4414128482 · doi:10.1177/03009858251367402

Geographical cluster of renal hamartomas in wild urban white-tailed jackrabbits ( <i>Lepus townsendii</i> )

2025· article· en· W4414128482 on OpenAlexafffundabout
Summer T. Hunter, Marie‐Anne Bründler, Sylvia Checkley, Susan C. Cork, Carolyn Legge, J. Scott Weese, Jamie L. Rothenburger

Bibliographic record

VenueVeterinary Pathology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of GuelphCanadian Wildlife FederationUniversity of Calgary
FundersCity of CalgaryUniversity of Calgary
KeywordsStromal cellMammalCluster (spacecraft)KidneyRenal cortexHamartoma

Abstract

fetched live from OpenAlex

), we autopsied 130 individuals that died near roadways in Calgary, Alberta, Canada. Renal hamartomas were present in 8 of 130 hares (6.2%; 95% confidence interval: 3.2%-11.7%). Most were unilateral (7/8); one case had bilateral lesions. Hamartomas are benign, tumor-like lesions comprised of normal tissue elements in abnormal amounts and arrangements. Macroscopically, hamartomas were white, tan, or pink-red, well-circumscribed, singular or multilobular, expansile nodules in the cortex or corticomedullary junction. Histologically, renal hamartomas consisted of well-demarcated mature stromal tissue with fibrous tissue and occasionally, adipocyte differentiation. These results represent a unique temporal and geographical cluster of a renal anomaly in an urban wildlife population. Renal hamartomas were not identified in other large studies of diseases in free-ranging leporids including hares. Contributing factors to this cluster remain unknown.

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 score0.038
Threshold uncertainty score0.075

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 studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.009
GPT teacher head0.231
Teacher spread0.222 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueVeterinary PathologySame topicWildlife Ecology and ConservationFrench-language works237,207