Origins of house reinfestation with Triatoma infestans after insecticide spraying in the Argentine Chaco using wing geometric morphometry
Bibliographic record
Abstract
Identifying the origins of insect vectors collected after community-wide residual insecticide applications is a relevant challenge in the Gran Chaco region where the main vector of Chagas disease Triatoma infestans usually reinfests human dwellings. Wing geometric morphometry was used to compare the right wings of 63 males and 54 females collected at 4 months post-spraying (MPS) with those from 165 males and 111 females collected before full-coverage spraying with pyrethroids in a well-defined rural area in Northeastern Argentina. Male and female wing centroid size resulted significantly larger at 4MPS than before interventions, but no significant changes in shape were detected. Metric disparity (variance of shape) varied significantly in males but not in females. Using shape variables, a relatively large fraction of post-spraying males (70%) and females (54%) could not be differentiated from those collected at the same source house or at the nearest infested house before interventions. Bugs collected at 4 and 8MPS in a persistently infested house were mainly assigned to the source house. These results support the hypothesis of persistent bug populations that survived the insecticide application at local spatial scales, and are consistent with the occurrence of vector control failures most likely related to moderate pyrethroid resistance. Wing geometric morphometry is a useful tool for identifying sources of reinfestation, but it is limited by the spatial structure found in the reference populations. Combined with field and genetic data, this approach may contribute to the understanding of the reinfestation process and improvement of vector control strategies.
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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 | 0.001 | 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".