Assessment of individual kidney function in a dog with congenital anomalies of the urinary tract
Bibliographic record
Abstract
A 21‐month‐old entire female labrador retriever was presented for polyuria, pollakiuria, haematuria and intermittent urinary incontinence. Clinical signs were absent during antibiotic treatment but reoccurred shortly after completion of a treatment course. Investigations detected bilaterally dilated ureters, right renal hypoplasia, left extramural ectopic ureter and right intramural ectopic ureter forming an ureterocoele. Blood tests revealed moderate renal azotaemia. 99m Tc‐DMSA (technetium‐99m‐dimercaptosuccinic acid) scintigraphy was used to quantify individual kidney function to carefully consider nephrectomy. The right kidney contributed to less than 2 per cent of the total kidney function. Individual kidney function assessed by 99m Tc‐DMSA scintigraphy was compared with CT‐based renal parenchyma volume as an equivalent to kidney function. In this case both diagnostic imaging techniques resulted in similar individual kidney function percentages. A right‐sided nephroureterectomy and a left‐sided neoureterocystostomy were performed. Surgical treatment successfully resolved the clinical signs. After surgery the dog’s chronic kidney disease remained stable at International Renal Interest Society chronic kidney disease stage 3.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".