The Effects of Different Lunar Phases on Sand Flies (Diptera: Psychodidae) Biodiversity in an Important Focus of Leishmaniasis, Southeast Iran
Bibliographic record
Abstract
Background: is endemic in most parts of Iran; however, its vector ecology has not been extensively studied. This study investigates the effects of lunar phases and climatic factors on the biodiversity and frequency of sand flies in various biotopes, with and without artificial light. Methods: Sand flies were collected using sticky paper traps in four lunar phases (new moon, first quarter, full moon, and last quarter). Alpha and beta diversity indices were calculated using the relevant formulas. Poisson regression analysis was used to study the relationship between lunar phases and climatic factors with the sand fly frequency. Results: In places with artificial light, the highest richness was observed in the new moon and the first quarter (S= 7), and the highest species evenness and Shannon-Wiener indices were observed in the last quarter (E= 0.464, H= 0.832) phases. But in areas without artificial light, the maximum value of richness was in the first quarter and full moon (S= 9), and the highest value of evenness and Shannon-Wiener was in the first quarter (E= 0.748, H= 1.645). Non-parametric tests revealed that among climatic factors, only wind speed exhibited a significant correlation with sand fly frequency. Conclusion: The highest diversity in biotopes with and without artificial light was observed in the last quarter and first quarter, respectively, and also, wind speed influenced the frequency and diversity of sand flies in different habitats, so in sand fly surveillance, it is crucial to consider these important factors.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".