PERSISTENT ORGANIC POLLUTANTS IN THE LIVERS OF MOOSE HARVESTED IN THE SOUTHERN NORTHWEST TERRITORIES, CANADA
Bibliographic record
Abstract
Moose (Alces alces) are an important traditional and spiritual resource for residents of the southern Northwest Territories and local residents are concerned about contaminants that may be present in the country foods they consume. As part of a larger program looking at contaminants in moose organs, we collected liver samples from moose harvested in two separate but adjoining regions within the Mackenzie River drainage area, the Dehcho and South Slave. We analyzed liver samples for a wide range of persistent organic pollutants (POPs) including polychlorinated biphenyls (PCBs), DDT related compounds, toxaphene, brominated diphenyl ethers (PBDEs) and perfluorinated alkyl substances (PFASs). Overall concentrations of major groups of POPs (total (Σ) PCBs, ΣPBDEs, ΣPFASs were consistently low (generally < 2 ng/g wet weight) in all samples and comparable to the limited data available from moose in Scandinavia. PFASs were the most prominent group with geometric means (range) of 1.3 (0.81–2.5) ng/g ww in the Dehcho and 0.93 (0.63–1.2) ng/g ww in the South Slave region. Decabromodiphenyl ether (BDE-209) was the most prominent PBDE congener, similar to that found in other arctic/subarctic terrestrial herbivores. In general, BDE-209 and PFASs, which are particle-borne and relatively non-volatile, were the predominant organic contaminants.
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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 | 0.001 |
| 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) | 0.001 | 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".