Morphological features of hepatic lipid changes in bearded dragons ( <i>Pogona vitticeps</i> ), and a proposed grading system
Bibliographic record
Abstract
Hepatic lipidosis is commonly diagnosed in pet bearded dragons ( Pogona vitticeps). However, there are no studies detailing the histological features of hepatic lipid changes in this species. This study describes the microscopic features of lipid change and details an associated scoring system. Histologic hepatic sections were retrospectively evaluated from 252 bearded dragons submitted for necropsy. Pathologic assessment was used to develop a grading scheme with 2 qualitative, 1 quantitative, and 6 semi-quantitative microscopic parameters, which were refined based on variability. The final grading system developed for diffuse and panlobular lipid accumulation included 2 semi-quantitative and 1 quantitative categories: percentage of hepatocellular vacuolation, fibrosis, and hepatocellular swelling, respectively. Hepatocellular swelling was indirectly quantified by counting the number of nuclei per unit area. There was a strong positive correlation ( P < .001) between the percentage of hepatocellular vacuolation and lipid content, a strong negative correlation ( P < .001) between nuclear count and lipid content, and a moderate correlation ( P < .001) between fibrosis and lipid content. Each category was given a numerical value ranging from 0 to 4, with the sum of each representing the final grade. Cutoff values stratified microscopic changes into mild (final grade 1–4), moderate (5–7), and severe (≥8). There was strong interrater agreement for assessment of vacuolization, fibrosis, and severity classification and moderate for hepatocellular swelling. This study documents the features of hepatic lipid changes in bearded dragons. Although a cutoff to differentiate pathologic from nonpathologic lipid accumulation could not be estimated, the proposed grading scheme can be used to inform future studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".