Identification, Distribution, and Habitat Suitability Models of Ixodid Tick Species in Cattle in Eastern Bhutan
Bibliographic record
Abstract
Tick infestation is the most reported parasitological problem in cattle in Bhutan. In May and June 2019, we collected ticks from 240 cattle in two districts of Eastern Bhutan. Tick presence, diversity, and infestation prevalence were examined by morphological identification of 3600 live adult ticks. The relationships between cattle, geographic factors, and infestation prevalence were assessed using logistic regression analyses. Habitat suitability for the tick species identified was determined using MaxEnt. Four genera and six species of ticks were found. These were Rhipicephalus microplus (Canestrini) (70.2% (95% confidence interval (CI): 68.7–71.7)), Rhipicephalus haemaphysaloides Supino (18.8% (95% CI: 17.5–20.1)), Haemaphysalis bispinosa Neumann (8.2% (95% CI: 7.3–9.1)), Haemaphysalis spinigera Neumann (2.5% (95% CI: 2–3)), Amblyomma testudinarium Koch (0.19% (95% CI: 0.07–0.4)), and a single unidentified Ixodes sp. Logistic regression indicated that the variables associated with infestation were: longitude and cattle age for R. microplus; latitude for R. haemaphysaloides; and altitude and cattle breed for H. bispinosa and H. spinigera. MaxEnt models showed land cover to be an important predictor for the occurrence of all tick species examined. These findings provide information that can be used to initiate and plan enhanced tick surveillance and subsequent prevention and control programs for ticks and tick-borne diseases in cattle in Bhutan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".