A field study of the use of methoprene for West Nile virus mosquito control
Bibliographic record
Abstract
The occurrence of vector-borne West Nile virus in Canada has resulted in the use of larvicides for widespread urban mosquito control. To determine the fate of larvicides in storm drainage systems, three catch basins in Toronto, Ontario were treated with methoprene (Altosid) pellets three times over the summer of 2003, at the recommended mosquito control dose of 0.7 g per catch basin. Daily monitoring included: methoprene concentration analysis, precipitation in the area, the presence of mosquito larvae, and the chemical composition of catch basin sumps. A model catch basin in the laboratory was also dosed with methoprene pellets and sampled daily to observe concentration over time under quiescent conditions. It was found that (1) the methoprene concentration at the catch basins fell below the minimum lethal concentration after one or two weeks after treatment; (2) rainfall flushed methoprene from the catch basins to the storm sewer outfall at concentrations lower than the level that may cause ecosystem damage; and (3) the methoprene concentrations in the experiments exhibited a double peak decay pattern. Key words: methoprene, Altosid, West Nile virus, larvicide, catch basin, Toronto.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".