Community-level responses by stream insects to neem products containing azadirachtin
Bibliographic record
Abstract
Abstract Outdoors sream channels weret teated with a commercial neem formulation, Neemixx® 4.5, and a neem extract (no formulation ingredients) to determine the effects on aquatic insect communities. An exposure period of 5 h was chosen to simulate the transient nature of pesticide residues in streams and rivers after aerial applications. Multivariate analytic procedures based on Bray-Curtis similarity matrices were used to compare community structure among the replicate channels 9 d after treatment. No significant differences in community structure were found among controls and channels treated with Neemix at an azadirachtin concentration of 0.28 mg/L, but a multivariate measure of community stress indicated an increase in variability among treated channels. Significant differences in community structure were found among controls and channels treated with Neemix at 0.84 and 2.54 mg/L, and this resulted from reductions in several key taxa. During subsequent experiments with a neem powder extract, the formulation ingredients of Neemix were at least partially responsible for the significant effects on community structure at 0.84 mg/L azadirachtin. No significant differences were found among controls and channels treated with the extract at 0.9 mg/L, whereas the community structure of aquatic insects in channels treated at 3.0 mg/L differed significantly from controls. In a Canadian forest pest-management context, the expected environmental concentration in water bodies of areas sprayed with azadirachtin at 50 g/ha is 0.035 mg/L.
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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".