<i>Dioctophyme renale</i> (giant kidney worm) in a dog: A review of a parasitic disease requiring surgical treatment
Bibliographic record
Abstract
Abstract Infection with the nematode Dioctophyme renale (giant kidney worm) in dogs and other mammals occurs following the ingestion of an aquatic host containing the infective larvae. This parasitic disease has no known effective pharmaceutical treatment. This case report describes a 7‐month‐old, entire, female Husky with a 2‐month history of haematuria and intermittent vomiting. An abdominal ultrasound examination and microscopic finding of eggs of D. renale in urine sediment helped to establish the diagnosis. The affected right kidney and retroperitoneal worms were removed by exploratory celiotomy. The sonographic features of the worms and a comprehensive review of the latest literature, suggesting future research topics on early serological diagnosis, medical treatment options and the most recent nephron‐sparing nephrotomy techniques (via nephroscopy or laparoscopy), are discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".