Assessing bioaccumulation with biomagnification factors from dietary bioaccumulation tests
Bibliographic record
Abstract
Despite the fact that the UN Stockholm Convention on persistent organic pollutants specifically acknowledges that Arctic ecosystems and Indigenous communities are particularly at risk due to biomagnification of contaminants in traditional foods, the bioconcentration factor (BCF) of substances in fish remains the preferred metric for identifying the biomagnification potential of organic substances. The BCF measures uptake of substances from water in water-breathing organisms, but not biomagnification of contaminants from food sources. The purpose of this study is to investigate how the biomagnification factor (BMF) can be used in bioaccumulation assessments. To address this question, data from dietary and aqueous bioaccumulation studies in fish were compiled for a wide range of substances in fish to (i) investigate the potential correlation between the BCF and the BMF for the same substance in the same fish species and (ii) investigate computational methods for deriving both the BMF and BCF from the results of empirical dietary bioaccumulation tests. The analysis concludes that (i) empirical correlations between the BCF and BMF are of limited use for bioaccumulation assessment; (ii) dietary bioaccumulation test results can be used for bioaccumulation screening; and supports the use of both the BMF and the BCF for assessing the bioaccumulation potential of substances in water-breathing organisms.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".