PARAMETERS FOR IDENTIFYING FAILURE OF PASSIVE TRANSFER IN SITATUNGA (TRAGELAPHUS SPEKII )
Bibliographic record
Abstract
Failure of passive transfer of immunity (FPT) leads to increased calf morbidity and mortality and requires intensive, time-sensitive, and often expensive management for nondomestic ruminants. Without species-specific information with which to make informed decisions, neonatal data from domestic ruminants are often extrapolated to nondomestic zoo-housed species. To date, there have been no studies evaluating FPT in sitatunga (Tragelaphus spekii). The goal of the present study was to establish parameters to characterize adequate passive transfer in sitatunga calves and compare them to published reference intervals in other species. Medical records of 22 sitatunga calves (12 female, 10 male) were reviewed. Seventeen of these calves were defined as “healthy,” having survived at least 60 days without colostrum administration or a plasma transfusion. Calf weight, serum glucose, serum gamma-glutamyl transferase (GGT), total protein (TP), globulin concentrations, and results of a zinc sulfate turbidity test (ZSTT) were noted where possible. Mean birth weight of healthy calves at 24 hr was 4.5 kg (range: 3.76.5 kg, n = 12). The mean blood glucose in healthy calves was 152 mg/dl (range: 80–182, n = 16), mean serum TP concentration was 5.9 g/dl (range: 4.9–7.5, n = 16), mean serum globulin concentration was 3.3 g/dl (range: 1.7–4.7, n = 17), and mean serum GGT concentration was 466 U/L (range: 91–1901, n = 16). A ZSTT was performed for 10 healthy calves, resulting in four negative ZSTT results despite having no clinical signs of FPT and the calves having been observed nursing before testing. Sitatunga appear to have lower values for normal FPT parameters than those developed for domestic cattle. This study illustrates the difficulty of cross-species comparisons, as even closely related species can vary greatly in biologic parameters.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".