The potential impact of climate on human exposure to contaminants in the Arctic
Bibliographic record
Abstract
Many northern indigenous populations are exposed to elevated concentrations of contaminants through traditional food and many of these contaminants come from regions exterior to the Arctic. Global contaminant pathways include the atmosphere, ocean currents, and river outflow, all of which are affected by climate. In addition to these pathways, precipitation, animal availability, UV radiation, cryosphere degradation and human industrial activities in the North are also affected by climate change. The processes governing contaminant behaviour in both the physical and biological environment are complex and therefore, in order to understand how climate change will affect the exposure of northern people to contaminants, we must have a better understanding of the processes that influence how contaminants behave in the Arctic environment. Furthermore, to predict changes in contaminant levels, we need to first have a good understanding of current contaminant levels in the Arctic environment, biota and human populations. For this reason, it is critical that both spatial and temporal trends in contaminant levels are monitored in the environment, biota and human populations from all the Arctic regions.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".