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Record W2113851314 · doi:10.1354/vp.43-3-276

Renal Tubular-cell Neoplasms in Black-footed Ferrets (<i>Mustela nigripes</i>)-38 Cases

2006· article· en· W2113851314 on OpenAlexaff
Stéphane Lair, Ian K. Barker, Kay G. Mehren, Elizabeth Williams

Bibliographic record

VenueVeterinary Pathology · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRenal and related cancers
Canadian institutionsUniversity of GuelphToronto Zoo
Fundersnot available
KeywordsPathologyBiologyPopulationMustela putoriusNeoplastic diseaseKidneyMedicinePhysiologyEndocrinology

Abstract

fetched live from OpenAlex

Thirty-eight cases of renal tubular cell neoplasms were diagnosed in 184 captive, adult (>1-year-old), black-footed ferrets (Mustela nigripes) examined from 1985 to 1996. This prevalence (20.7%) is one of the highest reported for this neoplasm in a population of animals. These tumors rarely metastasized (1/38), and usually were incidental postmortem findings, associated clinical disease being present in only 3 (8%) of the 38 cases. The prevalence of renal tubular cell neoplasms found at postmortem examination increased linearly with age, up to 67% in ferrets >8 years old. Both males (prevalence = 19%) and females (prevalence = 24%) were affected. Multiple renal tumors were common, and seven ferrets (18.4% of affected animals) had bilateral tumors. The cause of this neoplastic syndrome could not be determined. Since most of the animals affected by this condition were in their postreproductive years of life, the impact of this neoplastic syndrome on the captive propagation of this species is negligible.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.010
GPT teacher head0.230
Teacher spread0.220 · 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

Citations5
Published2006
Admission routes1
Has abstractyes

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