Retrospective Study of Melamine/Cyanuric Acid-Induced Renal Failure in Dogs in Korea between 2003 and 2004
Bibliographic record
Abstract
In early 2007, American pet food ingredients leading to nephrotoxic renal failure of dogs and cats raised serious concerns about the safety of pet foods. Major pet food companies recalled more than 1,000 commercial pet foods in consideration of pet safety. A similar pet food-associated outbreak of nephrotoxic renal failure occurred in Asia, in late 2003 and 2004, resulting in a similar extensive pet food recall. At that time, contamination of ingredients with a nephrotoxin-producing fungus at a pet food production facility was suspected. However, toxicologic evidence to substantiate a mycotoxicosis was lacking. Moreover, the renal lesions were not typical of those reported with fungal nephrotoxins. During 2003 and 2004, 14 dogs were presented to the Veterinary Medical Teaching Hospital of Konkuk University, Seoul, Korea, with renal failure and distinctive renal pathologic findings. Grossly, the kidneys were greenish in color with greenish uroliths in the renal pelvis or bladder. Histologically, characteristic crystals with pinwheel radiating striations were present in distal tubular segments. Toxicologic analysis identified melamine, cyanuric acid, and ammelide in deparaffinized formalin-fixed kidney samples.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".