Biodiversity Indices and Medically Importance of Ticks in North Khorasan Province, Northeast of Iran
Bibliographic record
Abstract
Background: Ticks are considered as the main vectors for the transmission of various pathogens such as relapsing fever and CCHF to humans. This study was investigated the biodiversity indices and medically importance of ticks in North Khorasan Province, Northeast of Iran during 2015–2019. Methods: Specimens were captured from infested ruminants including cows, sheep, and goats. Additionally, tick collections also were performed on non-domesticated creatures such as turtles, rodents, and hedgehogs. Specimens were identified using valid identification keys. Species diversity, species richness and evenness indices have been calculated to estimate species biodiversity of ticks. Results: A total of 1478 adult ticks were collected. The specimens were from two families: Ixodidae (90.05%) and Argasidae (9.95%), 6 genera and 17 species including: Rhipicephalus sanguineus (55.9%), Rhipicephalus bursa (13.4%), Hyalomma marginatum (9.5%), Hyalomma anatolicum (9.5%), Hyalomma asiaticum (0.2%), Hyalomma aegyptium (0.5%), Hyalomma scupense (1.3%), Hyalomma sp (1.2%), Haemaphysalis sulcata (0.7%), Haemaphysalis erinacea (0.1%), Haemaphysalis inermis (0.1%), Haemaphysalis punctata (0.2%), Haemaphysalis concinna (0.1% Boophilus annulatus (1.2), and Dermacentor marginatus (6.1%) among hard ticks as well as Argas persicus (91.8%) and Argas reflexus (8.2%) amongst soft ticks. Rhipicephalus sanguineus, Rh. Bursa, Hy. marginatum and Hy. anatolicum were known as the most frequent species of hard ticks. Tick’s species richness, Shannon diversity index and Simpson index in this area were S= 17, H’= 1.69, D= 0.294 respectively. Conclusion: Based on tick distribution veterinary authority, public health organizations and other officials should act for implementation of disease prevention.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".