Human-Landing Patterns of <I>Anopheles dirus</I> sensu lato (Diptera: Culicidae) in Experimental Huts Treated With DDT or Deltamethrin
Bibliographic record
Abstract
Anopheles dirus females landing on humans inside experimental huts treated with residual applications of DDT or deltamethrin were observed during the wet season in Pu Teuy Village, Kanchanaburi Province, western Thailand. Two identical experimental huts were constructed in the fashion of typical local rural Thai homes. Pretreatment (baseline) human-landing collections (HLC) in both huts showed an early evening peak of activity between 1900 and 2000 h with no significant difference in numbers of mosquitoes captured between huts over a period of 30 collection nights. During posttreatment HLC, female mosquitoes continued to show greater landing activity inside huts fitted with insecticide-treated panels during the first half of the evening compared with the second half. A greater number (proportion) of An. dirus females landed on humans in the hut treated with deltamethrin compared with DDT. Comparing pre- and posttreatment HLC, the DDT-treated hut showed a 79.4% decline in attempted blood feeding, whereas exposure to deltamethrin resulted in a 56.3% human-landing reduction. An odds ratio was performed to demonstrate the relative probability (risk) of mosquitoes entering and attempting to blood feed in the two treated huts compared with untreated control huts. Mosquitoes were approximately 0.47 times less likely to land on humans inside a DDT-treated hut compared with the deltamethrin-treated hut. Although both chemicals exerted strong excitatory responses, DDT appears to have a more pronounced and significant (P = 0.002) effect on behavior than deltamethrin, resulting in greater movement away from the insecticide source and thus potential reduction of blood-feeding activity.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".