Comparison of plasma total solids concentration as measured by refractometry and plasma total protein concentration as measured by biuret assay in pet rabbits and ferrets
Bibliographic record
Abstract
OBJECTIVE: To determine the agreement between plasma total solids (TS) concentration as measured by refractometry and plasma total protein (TP) concentration as measured by biuret assay in pet rabbits and ferrets. SAMPLE: 253 and 146 blood samples from 146 and 121 ferrets and rabbits, respectively, with results of CBC and plasma biochemical analyses. PROCEDURES: Data were collected from medical records regarding plasma TS and TP concentrations, PCV, plasma biochemical values, plasma appearance, and patient signalment. Agreement was determined between refractometer and biuret assay (reference method) values for plasma TS and TP concentration. Other variables were examined for an impact on this agreement. RESULTS: Mean ± SD plasma TP and TS concentrations were 6.4 ± 0.8 mg/dL and 6.6 ± 0.8 mg/dL, respectively, for rabbits and 6.3 ± 1.2 mg/dL and 6.4 ± 1.1 mg/dL for ferrets. On average, refractometer values overestimated plasma TP concentrations as measured by biuret assay. Plasma cholesterol, glucose, and BUN concentrations and hemolysis and lipemia had significant effects on this bias for ferrets; only BUN concentration had an effect on bias for rabbits given the available data. Other variables had no influence on bias. The limits of agreement were wider than the total allowable analytic error, and > 5% of the data points were outside acceptance limits, indicating that the 2 methods were not in clinical agreement. CONCLUSIONS AND CLINICAL RELEVANCE: Refractometer measurements of plasma TS concentration failed to provide a good estimation of biuret assay measurements of plasma TP concentration in rabbits and ferrets, suggesting that these 2 analytic methods and the results they yield cannot be used interchangeably in these species.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".