Development and testing of a new bioenergetic/bioaccumulation model for persistent organic pollutants in aquatic and terrestrial food webs
Bibliographic record
Abstract
This project developed and tested a bioenergetic/bioaccumulation model to predict concentrations, bioconcentration factors, bioaccumulation factors (BAF) and trophic magnification factors of persistent organic pollutants (POPs) in organisms in terrestrial and aquatic food webs. This is the first bioaccumulation model that conserves both mass of chemical and energy. This model was tested against concentrations of various POPs in wildlife of Canadian Arctic terrestrial and Lake Ontario aquatic food webs. The model is shown to predict BAFs of POPs in organisms that are in good agreement with observed BAFs as indicated by the model bias, which ranged from 0.62 to 5.31. A comparison of the behaviour of the new model to that of a previous aquatic BAF model by Arnot and Gobas (2004) shows that the models are comparable in their ability to predict BAFs. The model can be used for bioaccumulation screening of chemicals in both aquatic and terrestrial animals.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".