Examining impacts of current-use pesticides in Southern Ontario using in situ exposures of the amphipod<i>Hyalella azteca</i>
Bibliographic record
Abstract
In situ exposures with Hyalella azteca were used to assess impacts of current-use pesticides in Southern Ontario, Canada. Exposures were conducted over 2 growing seasons within areas of high pesticide use: 1 site on Prudhomme Creek and 3 sites on Twenty Mile Creek. Three sites on Spencer Creek, an area of low pesticide use, were added in the second season. Surface water samples were collected every 2 wk to 3 wk and analyzed for a suite of pesticides. Hyalella were exposed in situ for 1 wk every 4 wk to 6 wk, and survival and acetylcholinesterase (AChE) activity were measured. Pesticides in surface waters reflected seasonal use patterns: lower concentrations in spring and fall and higher concentrations during summer months. Organophosphate insecticides (chlorpyrifos, azinphos methyl, diazinon) and acid herbicides (2,4-dichlorophenoxyacetic acid [2,4-D], mecoprop) were routinely detected in Prudhomme Creek, whereas neutral herbicides (atrazine, metolachlor) dominated the pesticide signature of Twenty Mile Creek. Spencer Creek contained fewer pesticides, which were measured at lower concentrations. In situ effects also followed seasonal patterns: higher survival and AChE activity in spring and fall, and lower survival and AChE activity during summer months. The highest toxicity was observed at Prudhomme Creek and was primarily associated with organophosphates. The present study demonstrated that current-use pesticides in Southern Ontario were linked to in situ effects and identified sites of concern requiring further investigation.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".