The Impact of Selective Oviposition and Infection with <I>Plagiorchis elegans</I> on <I>Aedes aegypti</I> Pre-Imago Population Dynamics at Optimal Food Availability
Bibliographic record
Abstract
Progressive changes in the attraction of waters harboring pre-imago populations of Aedes aegypti exposed to different levels of the entomopathogenic digenean Plagiorchis elegans to ovipositing conspecific females were assessed under conditions of optimal food availability. The impact of ovipositional preference and parasitic infection on population structure and development was investigated. Probabilities that larvae progress from one stage to the next or die within 24 h were calculated for all life stages. Exposure to P. elegans cercariae did not significantly affect the attractiveness of larval-holding waters. Ovipositional preference increased significantly with growing bio-mass of the larval population, with the event of pupation and, in some cases, with late instar mortality. Exposure to various levels of the parasite significantly increased mortality of all instars, but most of the damage caused by the parasite occurred in the form of increased pupal mortality and decreased adult emergence. Exposure to the parasite significantly reduced the number of adults produced yet did not impair larval development. Thus, larval recruitment into environments containing P. elegans remains high, the structure of larval populations remains relatively normal, but few adults are produced.
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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".