Environmental contaminants assessment for frequently harvested migratory waterfowl in the Northeast Atlantic flyway
Bibliographic record
Abstract
Waterfowl serve as indicators of ecosystem health and represent a pathway of contaminant exposure for hunters who consume them. In the northeast Atlantic Flyway, data on baseline contaminant loads in waterfowl are lacking. We assessed five species of commonly harvested (and consumed) waterfowl for mercury, polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans, polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs), and per- and polyfluoroalkyl substances (PFAS). We found that Canada geese (Branta canadensis) and wood ducks (Aix sponsa) had lower contaminant burdens than mallards (Anas platyrhynchos), American green-winged teal (Anas carolinensis), and American black ducks (Anas rubripes). Regardless of species, all samples contained detectable levels of PCBs and at least one OCP and PFAS. Mercury and OCPs posed limited non-cancer risks to human consumers who follow current waterfowl consumption advisories. Based on a probabilistic risk assessment, lower consumption rates were required to reduce risks from PCBs compared to other contaminants. Protective human consumption advisories depend in part on the level of allowable cancer risk and whether contaminants were considered toxicologically to act individually or collectively. Accordingly, revisions to consumption advisories to protect public hunter health given these new data hinge upon risk management decisions. These data can be used to update waterfowl consumption advisories in the northeast Atlantic Flyway and inform future research into the health effects of legacy and contemporary contaminants on the sustainability of waterfowl populations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 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".