On the research needed to better characterise natural radioactivity accumulated in the Arctic by long-range atmospheric transport
Bibliographic record
Abstract
In recent decades, the Arctic has emerged as a bellwether for the necessity of global environmental protection. Even though far away from major industrial centres that generate pollution, the Arctic receives various pollutants through long-range transport in the atmosphere and oceans. Because there are very limited sources of such pollution in the Arctic, their presence is associated almost entirely with global sources outside the Arctic. The pollutants of industrial or man-made origins from outside of the Arctic are commonly identified as contaminants to the Arctic. Studies on environmental trends of mercury in the air and biota are one of the main subjects of research in the Arctic. Mercury is a global threat to human and environmental health. Most of the mercury studies focus on anthropogenic emissions of mercury and their transport and transformation in the environment. Anthropogenic emissions have been larger than natural emissions since the start of the industrial age about 200 y ago. Artisanal and small-scale gold mining and coal burning for power generation and industrial use are the major sources of anthropogenic mercury emissions to the air. It is estimated that current anthropogenic sources are responsible for ∼30 % of annual emissions of mercury to the air. Another 10 % comes from natural geological sources, and the rest (60 %) is from 'reemissions' of previously released mercury that has built up over long periods of time in surface soils and oceans(1). The Arctic is a remote region, far from major human sources of mercury releases. Despite this, a substantial amount of the mercury is carried into the Arctic region via long-range transport by air and water currents from human sources at lower latitudes. Owing to their traditional local diet particularly from the animals at the top of the Arctic's aquatic food chain where inorganic mercury is transformed into the more toxic form of methylmercury, some Arctic peoples receive high dietary exposure to mercury, and this is raising concerns for human health(2). This situation has called for global actions for air pollution controls, more stringent regulations and improvement of technology in major industrial countries, as evidenced by the Minamata Convention on Mercury formally adopted as international law in October 2013. The new treaty aims to further cut mercury emissions and releases and is the first global convention on environment and health. Long-term monitoring of mercury levels in the air at Canadian monitoring sites(3) has demonstrated a clear declining trend in the past 15 y, even given the ever increasing use of coal for power generation and industry, especially in Asia.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".