Quantitative Structure Activity Relationships for Predicting the Bioaccumulation of POPs in Terrestrial Food‐Webs
Why this work is in the frame
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Bibliographic record
Abstract
Abstract K OW based QSARs are used to assess the bioaccumulation potential of thousands of commercial chemicals in Canada and internationally. The QSARs, which are based on information from aquatic organisms, identify chemicals with a log K OW >5 to have a potential to biomagnify in food‐chains. This study investigates whether K OW based QSARs are also effective in identifying biomagnifying chemicals in terrestrial food‐chains. First, a terrestrial bioaccumulation model is developed and used to hypothesize the general relationship between the chemical's octanol‐air and octanol‐water partition and its biomagnification potential. Secondly, field observations of the bioaccumulation of persistent organic pollutants in wolves are used to test the hypothesis and explore the fundamental differences between QSARs for bioaccumulation in aquatic and terrestrial food‐chains. The results indicate that (i) QSARs for bioaccumulation in terrestrial food‐chains should include both octanol‐air (K OA ) and octanol water partition coefficients (K OW ); (ii) chemicals with a log K OA >approximately 5 can biomagnify in terrestrial food‐chains if log K OW >2 and the rate chemical transformation or metabolism is low; (iii) biomagnification factors in terrestrial food‐chains are much greater than those in aquatic food‐chains; (iv) biomagnification factors of very hydrophobic substances (log K OW >7) in terrestrial biota do not drop off with increasing K OW as has been observed in aquatic biota. The relevance of these findings is that current regulations and protocols may misidentify (i) low K OW but high K OA chemicals as having no bioaccumulation potential and (ii) very hydrophobic (log K OW >8.5) which appear not to biomagnify in aquatic organisms but have the potential to biomagnify in terrestrial food‐chains. Considering that 67.9% of the approximately 12 000 organic chemicals on Canada's Domestic Substances List exhibit high K OA but low K OW , this represents a major gap in our methods for screening bioaccumulative substances.
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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 | 0.003 |
| 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) | 0.000 | 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