Effects of an azinphos-methyl runoff event on macroinvertebrates in the Wilmot River, Prince Edward Island, Canada
Bibliographic record
Abstract
Abstract High levels of azinphos-methyl (0.4–0.8 µg/L) were detected in the Wilmot River, Prince Edward Island, Canada, following runoff from an agricultural field after a heavy rainfall on 19 July 2002. Benthic macroinvertebrate abundance and diversity were sharply lower in samples collected 1 d after the event compared with samples collected in the same manner in July or October 2001. The greatest effects were noticed on the aquatic insects, whose abundance declined from >10 000 individuals per 3-min kick sample in July 2001 to <900 individuals per 3-min kick sample in July 2002. One family of Diptera, one family of Plecoptera, and three families of Trichoptera disappeared entirely from the study reach after the runoff event, and several other families were severely depleted in number. This led to low taxonomic similarity values between the communities before and after the runoff event and a change relative to reference streams on PEI. Examination of biological metrics (including indices such as % EPT (Ephemeroptera, Plecoptera, or Trichoptera), % chironomids, % burrowers, etc.) confirmed that aquatic insects were more heavily targeted by the insecticide than non-insect invertebrates. This resulted in a shift in the community towards non-insect taxa that were better able to avoid or tolerate this type of pollution.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".