Bioassay for Detection of Dichlorvos Insecticide in Air in Alfalfa Leafcutting Bee (Megachile Rotundata F.) Incubators
Bibliographic record
Abstract
Abstract Dichlorvos is an insecticide used in slow-release plastic strips for controlling chalcid wasp parasites, such as Pteromalus venustus Walker, in incubators used to raise alfalfa leafcutting bees (Megachile rotundata F.). Beekeepers need a practical method to detect dichlorvos in air and verify that it has dissipated to levels acceptable for worker re-entry and for the bees to emerge. We evaluated three methods for analysis of the dichlorvos concentration in air. Vapor sampling tubes using a manually operated pump or diffusion collection had insufficient sensitivity in the concentration range of interest. Air samples collected using battery powered pumps were analyzed by liquid chromatography/tandem mass spectrometry (LC/MS/MS), which was accurate and sensitive, but too costly and slow for practical use. Finally, a convenient bioassay for detecting dichlorvos in air was developed using leafcutting bees and verified by comparison with the results obtained by LC/MS/MS for a series of dose levels. The bioassay is simple enough to be done by the beekeeper on-site, is inexpensive, and gives results within 1 h. The LC 50 for dichlorvos vapor in air after 1 h of exposure was 273.2 μg/m 3 by the probit regression method or 277.3 μg/m 3 by the logit regression method.
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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".