Renal azotemia and associated haematobiochemical findings in a Labrador Retriever dog with Babesia gibsoni infection
Bibliographic record
Abstract
A 2-year-old male Labrador retriever was presented to the Veterinary Clinical Complex, College of Veterinary Science, AAU, Khanapara with a history of anorexia, fever, lethargy, dark yellow urine and tick infestation (+++). Clinical examination revealed fever (103.2ºF), tachycardia with laboured breathing, pale mucous membrane, dark yellow urine, melena with swollen superficial lymph nodes. Blood samples collected were subjected to microscopy, haemato-biochemical analysis and PCR. Babesia gibsoni was detected on blood smear examination and confirmed by polymerase chain reaction (PCR). Haemato-biochemical analysis showed anaemia, leucocytosis with increased level of liver and kidney markers. Ultrasonography of kidneys revealed hyperechoic and thickened renal cortex. The dog was initially treated with Imidocarb dipropionate prior to the presentation. Based on clinical signs, microscopy, PCR, haemato-biochemical changes and diagnostic imaging, and earlier history of treatment the present case was confirmed as renal azotemia associated with babesiosis. Treatment was initiated using Diminazene diaceturate, Doxycycline and renal conservative therapy. Following treatment, the dog showed clinical recovery with improvement in the haemato-biochemical parameters.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".