A Serological Survey of Ruminant Livestock in Kazakhstan During Post-Soviet Transitions in Farming and Disease Control
Bibliographic record
Abstract
The results of a serological survey of livestock in Kazakhstan, carried out in 1997--1998, are reported. Serum samples from 958 animals (cattle, sheep and goats) were tested for antibodies to foot and mouth disease (FMD), bluetongue (BT), epizootic haemorrhagic disease (EHD), rinderpest (RP) and peste des petits ruminants (PPR) viruses, and to Brucella spp. We also investigated the vaccination status of livestock and related this to changes in veterinary provision since independence in 1991. For the 2 diseases under official surveillance (FMD and brucellosis) our results were similar to official data, although we found significantly higher brucellosis levels in 2 districts and widespread ignorance about FMD vaccination status. The seroprevalence for BT virus was 23%, and seropositive animals were widespread suggesting endemicity, despite the disease not having being previously reported. We found a few seropositives for EHDV and PPRV, which may suggest that these diseases are also present in Kazakhstan. An hierarchical model showed that seroprevalence to FMD and BT viruses were clustered at the farm/village level, rather than at a larger spatial scale. This was unexpected for FMD, which is subject to vaccination policies which vary at the raion (county) level.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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 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".