Weight of evidence assessment of effects of sulfoxaflor on aquatic invertebrates: sulfoxaflor environmental science review part II
Bibliographic record
Abstract
Effects of sulfoxaflor (SFX) on aquatic invertebrates were assessed by comparing concentrations predicted to occur in or measured in surface waters to thresholds for adverse effects. Due to the specific mode of toxic action, fishes are relatively tolerant of the effects of SFX. Daphnia magna with an LC50 of 378 mg SFX L−1 (SD = 19.13) was similarly tolerant of the effects of SFX, while the LOEC was >110 mg SFX L−1. A threshold for effects on aquatic insects, based on the chironomid midge, C. tentans, had LOAEL and NOAEL values of 0.0455 and 0.0618 mg L−1, respectively. The acute-to-chronic ratio was 18. Simulation models and parameters selected for a range of applications to crops predicted environmental concentrations (EECs) in surface waters to range from 2.2 to 7.7 µg L−1. Based on these EECs, the maximum hazard quotient (HQ) was 0.11, which is less than the US EPA level of concern (LOC) of 0.5, which would normally be the threshold to trigger regulatory action or higher-tier assessments. The risks posed by SFX to aquatic organisms are predicted to be de minimis. Hazard quotients based on EEC values predicted in the standard, USEPA farm pond estimated by use of the Pesticides in Water Calculator (PWC version 1.52) for scenarios of maximum application rates for cotton and LOAEL and NOAEL values for aquatic insects for SFX were less than or similar to those for other insecticides including neonicotinoids and organophosphorus compounds.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".