AMEG: the new SETAC advisory group on aquatic macrophyte ecotoxicology
Bibliographic record
Abstract
INTRODUCTION AND BACKGROUND: Primary producers play critical structural and functional roles in aquatic ecosystems; therefore, it is imperative that the potential risks of toxicants to aquatic plants are adequately assessed in the risk assessment of chemicals. The standard required macrophyte test species is the floating (non-sediment-rooted) duckweed Lemna spp. This macrophyte species might not be representative of all floating, rooted, emergent, and submerged macrophyte species because of differences in the duration and mode of exposure; sensitivity to the specific toxic mode of action of the chemical; and species-specific traits (e.g., duckweed's very short generation time). DISCUSSION AND PERSPECTIVES: These topics were addressed during the workshop entitled "Aquatic Macrophyte Risk Assessment for Pesticides" (AMRAP) where a risk assessment scheme for aquatic macrophytes was proposed. Four working groups evolved from this workshop and were charged with the task of developing Tier 1 and higher-tier aquatic macrophyte risk assessment procedures. Subsequently, a SETAC Advisory Group, the Macrophyte Ecotoxicology Group (AMEG) was formed as an umbrella organization for various macrophyte working groups. The purpose of AMEG is to provide scientifically based guidance in all aspects of aquatic macrophyte testing in the laboratory and field, including prospective as well as retrospective risk assessments for chemicals. As AMEG expands, it will begin to address new topics including bioremediation and sustainable management of aquatic macrophytes in the context of ecosystem services.
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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 | 0.021 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.024 | 0.009 |
| Insufficient payload (model declined to judge) | 0.098 | 0.050 |
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".