The influence of larval density, food stress, and parasitism on the bionomics of the dengue vector Aedes aegypti (Diptera: Culicidae): implications for integrated vector management
Bibliographic record
Abstract
New larval control strategies for integrated vector management of Aedes aegypti are in high demand, including the use of biological control agents. Exposure of Aedes aegypti to parasites, starvation, and overcrowded conditions during larval development reduces the probability of survival to eclosion, can directly affect fitness parameters such as adult size and fecundity, and can affect the size, provisioning, and viability of eggs produced by females. We compared these parameters after exposing larvae to 1) abundant food at low larval densities, 2) food deprivation and high larval density, and 2) infection with the endoparasite Plagiorchis elegans, an entomopathogenic digenean trematode. Female mosquitoes that eclosed from larval conditions of starvation and overcrowding were smaller and laid fewer and smaller eggs than controls. The proportion of females to complete an oviposition cycle was reduced in the P. elegans-infected treatment group. Parasite load was negatively correlated with wing length and egg size. Infection of Ae. aegypti with P. elegans has sublethal effects and may reduce population-level reproductive output, but one-time low-density P. elegans exposure does not have sufficient effect on Ae. aegypti fitness parameters to be considered a viable biocontrol option.
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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".