An Arctic Terrestrial Food-Chain Bioaccumulation Model for Persistent Organic Pollutants
Bibliographic record
Abstract
A model representing the bioaccumulation of persistent organic pollutants (POPs) in arctic terrestrial mammalian food-chains is developed, parametrized, tested, and analyzed. The model predicts concentrations of POPs in lichen, caribou (Rangifer tarandus), and wolf (Canis lupus) food-chains of Canada's central and western arctic region from measured concentrations in air and snowpack meltwater. The model accounts for temporal and seasonal variation in diet composition, life-stage, body weight, and fat content over the life-span of the animal. Model predicted concentrations of 25 organic chemicals forecasted for caribou and wolves from Cambridge Bay (69 degrees 07' N 105 degrees 03' W), Inuvik (68 degrees 18' N 133 degrees 29' W) and Bathurst Inlet (64 degrees 15' N 113 degrees 07' W) are shown to be in good agreement with the observed data. The model illustrates a strong relationship between biomagnification factors and chemical K(OA) and illustrates the effect of age, sex, and temperature on POPs bioaccumulation. Model results show that POPs with K(OA)s < 10(5) do not biomagnify in arctic terrestrial food-chains, while substances that exhibit log K(OA)s > 5 and also exhibit a log K(OW) > 2, show significant bioaccumulation in arctic terrestrial food-chains. The model shows that persistent low K(OW) (K(OW)s < 10(5)) but high K(OA) substances such as beta-HCH, 1,2,4,5 tetrachlorobenzene, and beta-endosulfan biomagnify in terrestrial mammals.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".