Spatiotemporal cluster and incidence analysis of cattle mortality caused by bovine babesiosis in Styria, Austria, between 1998 and 2016
Bibliographic record
Abstract
Reported fatal cases of bovine babesiosis (syn.: piroplasmosis, red water fever) in cattle were analyzed to identify spatial and temporal clusters of their incidence in the Austrian province of Styria. Data were collected within a governmental babesiosis compensation program. Diagnosis was performed using a standardized necropsy protocol. Between 1998 and 2016, a total of 1257 cases of fatal babesiosis were registered and compensated. Within the study interval, annual numbers of fatal babesiosis differed significantly among municipalities. Spatiotemporal analysis covering the entire study period revealed one high-risk cluster in the western and central northern region of Styria and a low-risk cluster in the southeastern part of Styria. Annual temporal analysis demonstrated that cases accumulated in June. Annual spatial analysis revealed consistently that cases mainly occurred in the western and central northern regions, whereas they occurred rarely in the southeastern regions. These results should increase awareness and facilitate protective actions against ticks during certain time periods and geographic areas.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".