METAALICUS : mercury experiment to assess atmospheric loading in Canada and the United States
Bibliographic record
Abstract
Mercury emitted from coal-fired utilities is one of the major sources of anthropogenic mercury in the environment. Recently proposed control strategies for these emissions are expected to cost several billion dollars per year for North America alone. The major objective in controlling mercury emissions is to decrease levels of mercury in fish consumed by humans. However, since the actual relationship between atmospheric mercury deposition and fish mercury is still unknown, a unique whole-ecosystem study was conducted to address this issue. During the course of this study at the experimental Lakes Area in northwestern Ontario, the load of mercury in a small lake was increased by a factor of four to simulate the atmospheric loadings to lakes in northeastern North America. The mercury was added as three different stable isotopes to determine the most important sources of mercury to fish. The isotopes also made it possible to compare the availability of newly deposited mercury with old mercury stored in lake sediments and soils by analyzing mercury isotope patterns in biota. The response time in a catchment area to an increase in the rate of atmospheric deposition of mercury was calculated to determine if newly deposited mercury behaves in the same way as mercury that has accumulated in upland soils over many years.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".