ESTABLISHING REFERENCE INTERVALS FOR SERUM INFLAMMATORY MARKERS AND INVESTIGATING THEIR STORAGE STABILITY AND CLINICAL UTILITY IN ASIAN WILD HORSES (EQUUS FERUS PRZEWALSKII) UNDER MANAGED CARE
Bibliographic record
Abstract
Acute phase proteins (APPs) are commonly used in domestic equine practice, where they rise rapidly in response to inflammation and decrease soon after resolution. This response provides useful information to identify, monitor, and prognosticate a variety of inflammatory conditions. Asian wild horses (Equus ferus przewalskii) are an endangered relative of the domestic horse, and APP reference intervals (RI) and clinical utility in this species are not well documented. This study used serum samples from clinically healthy Asian wild horses under managed care to establish RI for serum amyloid A (SAA, n = 21) using an equine SAA assay and haptoglobin (HP, n = 23) using a proprietary assay. The utility of SAA and HP in identifying inflammation in clinically abnormal horses was assessed, and storage stability of these analytes under refrigerated conditions was determined. The RIs established in this study were 0.3–6.8 mg/L for SAA and 0–3.25 g/L for HP. Six clinically abnormal cases were retrospectively assessed using the RI established in this study. One case of pituitary neoplasia showed elevated SAA levels, one case of maxillary lip phaeohyphomycosis and concurrent endometritis showed elevations in SAA and HP, and one case of chronic laminitis had elevated SAA. Storage stability of SAA and HP were assessed at 4°C over 7 d. SAA significantly decreased between Time 0 h and Time 72 h, but increased again at 7 d with no significant difference between Time 0 h and Time 7 d. Because of the initial decrease in SAA concentration over the first 72 h, it is recommended that SAA is analyzed within 48 h if freezing or immediate analysis is not possible. There was no significant difference between HP between Time 0 h and Time 7 d, suggesting stability of this analyte over this period if freezing or immediate analysis is not possible.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".