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Hypercalcaemia associated with granulomatous lymphadenitis and elevated 1,25 dihydroxyvitamin D concentration in a dog

2006· article· en· W2045381207 on OpenAlexaboutno aff
Richard J. Mellanby, Paul Mellor, E. J. Villiers, M. E. Herrtage, David Halsall, Stephen O’Rahilly, P. E. McNeil, A.P. Mee, Jacqueline Berry

Bibliographic record

VenueJournal of Small Animal Practice · 2006
Typearticle
Languageen
FieldMedicine
TopicLymphadenopathy Diagnosis and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHypercalcaemiaMedicineParathyroid hormonePathologyHistopathologyLymph nodeLymphInternal medicineGastroenterologyCalcium

Abstract

fetched live from OpenAlex

A seven-year-old Labrador was presented with weight loss and mild generalised lymphadenopathy. Histopathology of an excised lymph node by the referring veterinarian demonstrated granulomatous lymphadenitis. At the time of referral, fine-needle aspirates of the lymph nodes confirmed the presence of ongoing granulomatous inflammation. Further investigations revealed marked hypercalcaemia, a low parathyroid hormone concentration, a parathyroid hormone related protein concentration within the reference range, and an elevated serum concentration of 1,25 dihydroxyvitamin D. An underlying cause of the granulomatous lymphadenitis could not be identified. The clinical signs, hypercalcaemia and elevated serum concentrations of 1,25 dihydroxyvitamin D resolved following prednisolone treatment. In contrast to dogs, hypercalcaemia occurred secondarily to granulomatous disease and elevated 1,25 dihydroxyvitamin D concentrations is a well-recognised condition in human beings. To the authors' knowledge, this is the first case report to describe elevated serum calcium and 1,25 dihydroxyvitamin D concentrations in a dog with histologically confirmed granulomatous disease.

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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.001
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 head0.246
Teacher spread0.237 · 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

Citations30
Published2006
Admission routes1
Has abstractyes

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