Urine specific gravity values in clinically healthy young pet ferrets (<i>Mustela furo</i>)
Bibliographic record
Abstract
OBJECTIVES: To determine urine specific gravity values in clinically healthy pet ferrets and explore possible associations with sex, sampling techniques, hydration status and urine analytes. METHODS: Sixty-nine entire ferrets of both sexes, under one year of age, were included in this study. Physical examination, complete blood count, blood biochemistry, urine microscopy, urine dipstick and urine specific gravity were performed on all ferrets. Urine specific gravity was determined using a handheld urine refractometer. Statistical analysis was performed to determine urine specific gravity value intervals and to test for associations with sex, sample collection method, packed cell volume, plasma total protein concentrations and urine analytes. RESULTS: Urine specific gravity differed by sex in ferrets as females exhibited a lower urine specific gravity (P<0·001). There was no significant correlation between urine specific gravity, sampling method, packed cell volume/total protein and urine dipstick analytes. Mean urine specific gravity reported in this study was 1·051 for entire males (sd ±9; range 1·034 to 1·070) and 1·042 for entire females (sd ±8; range 1·026 to 1·060). CLINICAL SIGNIFICANCE: Results of this study may allow clinicians to have a more accurate evaluation of the ability of those animals to concentrate urine by comparing their urine specific gravity results to those obtained from this cohort of clinically healthy animals.
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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 | 0.001 | 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".