The role of field dust in pesticide drift when pesticide‐treated maize seeds are planted with vacuum‐type planters
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract BACKGROUND Neonicotinoid‐contaminated dust escaping pneumatic seeders causes exposure to non‐target organisms such as pollinators. Two sources of dust have been reported: abrasion by talc which is added as seed lubricant during planting, and seed‐to‐seed abrasion occurring during seed handling, distribution and planting. We report a third important source that warrants remediation. Here, soil dust stirred up by planters was found to enter the vacuum air intake near seed metering devices. RESULTS The mean quantity of dust collected from the exhaust of a commercial pneumatic planter over a number of field sites and situations was 46 g ha −1 , ranging from 5.8 to 184.2 g ha −1 . While the clothianidin concentration in exhaust dust declined with increasing quantity of dust, total clothianidin recovered increased linearly within the study parameters. Up to 2.4 g ha −1 of clothianidin was recovered from planter exhaust, representing approximately 12.6% of the active ingredient applied to seed. A similar pattern occurred in the laboratory on a single standing planter unit using diatomaceous earth as surrogate field dust. CONCLUSION Field dust in pneumatic metering systems contributes significantly to clothianidin contamination in planter exhaust by seed abrasion. Adding diatomaceous earth as surrogate field dust to the Heubach seed dust protocol accounted for field dust abrasion and distinguished anti‐abrasive properties of seed treatments. © 2017 Society of Chemical Industry
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it