Practical advice for selecting or determining trophic magnification factors for application under the European Union Water Framework Directive
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Bibliographic record
Abstract
Abstract European Union Directive 2013/39/EU, which amended and updated the Water Framework Directive (WFD; 2000/60/EC) and its daughter directive (2008/105/EC), sets Environmental Quality Standards for biota (EQSbiota) for a number of bioaccumulative chemicals. These chemicals pose a threat to both aquatic wildlife and human health via the consumption of contaminated prey or the intake of contaminated food originating from the aquatic environment. EU member states will need to establish programs to monitor the concentration of 11 priority substances in biota and assess compliance against these new standards for the classification of surface water bodies. An EU-wide guidance effectively addresses the implementation of EQSbiota. Flexibility is allowed in the choice of target species used for monitoring to account for both diversity of habitats and aquatic community composition across Europe. According to that guidance, the consistency and comparability of monitoring data across member states should be enhanced by adjusting the data on biota contaminant concentrations to a standard trophic level by use of the appropriate trophic magnification factor (TMF), a metric of contaminant biomagnification through the food web. In this context, the selection of a TMF value for a given substance is a critical issue, because this field-derived measure of trophic magnification can show variability related to the characteristics of ecosystems, the biology and ecology of organisms, the experimental design, and the statistical methods used for TMF calculation. This paper provides general practical advice and guidance for the selection or determination of TMFs for reliable application within the context of the WFD (i.e., adjustment of monitoring data and EQS derivation). Based on a series of quality attributes for TMFs, a decision tree is presented to help end users select a reasonable and relevant TMF. Integr Environ Assess Manag 2019;15:266–277. © 2018 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC)
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it