Ultrasonographic evaluation of preprandial and postprandial gallbladder volume in healthy cats
Bibliographic record
Abstract
OBJECTIVE: To noninvasively assess the influence of ingestion of a standard meal on gallbladder volume (GBV) in healthy cats. ANIMALS: 10 healthy adult domestic shorthair cats (4 neutered females, 5 neutered males, and 1 sexually intact male). PROCEDURES: Nonsedated cats were positioned in dorsal and left lateral recumbency to obtain ultrasonographic measurements of the gallbladder via the subcostal and right intercostal acoustic windows, respectively. Gallbladder volume was calculated from linear measurements by use of an ellipsoid formula (volume [mL] = length [mm] × height [mm] × width [mm] × 0.52). Measurements were recorded after food was withheld for 12 hours (0 minutes) and at 5, 15, 30, 45, 60, and 120 minutes after cats were fed 50 g of a standard commercial diet (protein, 44.3%; fat, 30.3%; and carbohydrate, 15.6% [dry matter percentage]). RESULTS: Agreement between gallbladder linear measurements or GBV obtained from the subcostal and right intercostal windows was good. Feeding resulted in linear decreases in gallbladder linear measurements and GBV. Via the subcostal and intercostal windows, mean ± SD GBV was 2.47 ± 1.16 mL and 2.36 ± 0.96 mL, respectively, at 0 minutes and 0.88 ± 0.13 mL and 0.94 ± 0.25 mL, respectively, at 120 minutes. Gallbladder width most closely reflected postprandial modification of GBV. CONCLUSIONS AND CLINICAL RELEVANCE: Results indicated that ultrasonographic assessment (via the subcostal or right intercostal acoustic window) of postprandial changes in GBV can be used to evaluate gallbladder contractility in cats. These data may help identify cats with abnormal gallbladder emptying.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".