Future human health research directions for the Canadian Northern Contaminants Program
Bibliographic record
Abstract
Studies conducted in the mid-1980s and early 1990s demonstrated that persistent organic pollutants (POPs) and metals were reaching the Arctic ecosystem at unexpectedly high levels, many of which had no Arctic or Canadian sources. Epidemiological and toxicological studies in Canada and in other countries have found that these contaminants may pose a risk to human health. The objective of this paper is to provide the foundation for the discussion on future northern human health research under the Northern Contaminants Program (NCP) in Canada. This short discussion of human health priorities will help guide a path forward for future northern human health research in Canada to address on-going and new health concerns related to contaminants exposure in the Canadian Arctic.
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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 | 0.032 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.015 | 0.007 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.023 | 0.002 |
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".