Refined avian risk assessment for aldicarb in the United States
Bibliographic record
Abstract
Aldicarb was recently reviewed by the US Environmental Protection Agency (USEPA) for re-registration eligibility. In this paper, we describe a refined avian risk assessment for aldicarb that was conducted to build upon the screening-level methods used by USEPA. The goal of the refined ERA was to characterize and understand better the risks posed by aldicarb to birds in areas where the pesticide is applied. Aldicarb is a systemic insecticide sold in granular form under the trade name Temik. It is applied directly to soil and is used to control mites, nematodes, and aphids on a variety of crops (e.g., cotton, potatoes, peanuts). Consumption of grit is necessary for proper digestion in many bird species, particularly for granivores and insectivores. Thus, aldicarb granules may be mistaken for grit by birds. The Granular Pesticide Avian Risk Assessment Model (GranPARAM) is described in a companion paper and was used to estimate the probability and magnitude of effects to flocks of birds that frequent aldicarb-treated fields. One hundred thirty-five exposure scenarios were modeled that together include a range of bird species, crops, application methods and rates, and regions in the United States. The results indicated that, even for the most sensitive bird species, the risks associated with the agricultural use of granular aldicarb are negligible to low. There are several reasons for the limited risk: 1) the Temik formulation includes a gypsum core and a graphite coating and is black in color, all of which have been shown to be unattractive to birds, and 2) the pesticide is applied subsurface and rapidly dissolves following contact with water. The fact that no bird kill incidents involving appropriate label uses of aldicarb have been conclusively documented in the United States over its 38 years of use supports the results of this refined risk assessment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 teacher head, 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".