Renal Lesions of Nondomestic Felids
Bibliographic record
Abstract
To comprehensively evaluate the occurrence of renal lesions in a variety of nondomestic felids, necropsy cases from 1978 to 2008 were reviewed from a municipal zoo and a large cat sanctuary for those in which the kidneys were examined histologically. Seventy exotic felids were identified (25 tigers, 18 lions, 6 cougars, 5 leopards, 3 snow leopards, 3 clouded leopards, 3 Canadian lynx, 2 ocelots, 2 bobcats, 2 cheetahs, 1 jaguar), and their histologic renal lesions were evaluated and compared. The most common lesion was tubulointerstitial nephritis (TIN); 36 of 70 (51%) cats were affected to some degree. Lymphocytic interstitial nephritis was the most common lesion in the tigers (9 of 25, 36%) and was rarely seen in other species. Although the renal pelvis was not available for all cats, 28 of 47 (60%) had some degree of lymphocytic pyelitis. There was no significant association between the presence of pyelitis and that of TIN. Only 1 cat had pyelonephritis. Renal papillary necrosis was present in 13 of 70 (19%) cats and was significantly associated with historical nonsteroidal anti-inflammatory drug treatment (odds ratio, 7.1; 95% confidence interval, 1.9 to 26.8). Only 1 cat (lion) had amyloid accumulation, and it was restricted to the corticomedullary junction. Primary glomerular lesions were absent in all cats. Intraepithelial pigment was identified in many of the cats but was not correlated with severity of TIN. Despite several previous reports describing primary glomerular disease or renal amyloidosis in exotic felids, these lesions were rare to absent in this population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".