ULTRASONOGRAPHIC MEASUREMENT OF KIDNEY‐TO‐AORTA RATIO AS A METHOD OF ESTIMATING RENAL SIZE IN DOGS
Bibliographic record
Abstract
Renal size is an important parameter in the assessment of renal disease in dogs. However, because of the great variability in body conformation, absolute renal measurements cannot solely be used when evaluating kidneys with ultrasonography. The use of a ratio comparing renal length and aortic luminal diameter (K/Ao) was investigated. After confirming the reproducibility of these measurements, K/Ao ratios were obtained in 92 dogs without clinical evidence of renal disease. Left and right K/Ao ratios were statistically similar. Based on 95% confidence intervals, renal size should be considered reduced if the K/Ao ratio is < 5.5 and increased when > 9.1.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Ultrasound kidney-to-aorta ratio in dogs; a veterinary measurement study, with 'reproducibility' in the assay sense.
This evaluates a veterinary ultrasound measurement method, not research methodology as an object.
Veterinary ultrasound method for canine renal size; measurement reproducibility is assay sense, not metaresearch.
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 | 0.002 | 0.006 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".