Mercury concentrations and potential methylation rates in Lake Erie
Bibliographic record
Abstract
Abstract Little is known about external and internal loading and cycling of bioaccumulative methylmercury in Lake Erie, despite the lake having a world-renowned sport fishery. During the summer/early fall of 2018 to 2021, concentrations and fluxes of total mercury and methylmercury in the water column were examined near the Detroit and Maumee River discharges into western Lake Erie, as well as the junction between Sandusky Bay and central Lake Erie. Average unfiltered total mercury concentrations were similar near the Detroit River (5.4 ± 0.8 pM) and Sandusky Bay inputs (5.3 ± 0.9 pM), which were less than half of those near the Maumee River mouth (11.6 ± 2.8 pM). Similarly, unfiltered methylmercury concentrations near the Detroit River (0.29 ± 0.09 pM) and Sandusky Bay inputs (0.24 ± 0.06 pM) were less than half of those near the Maumee River mouth (0.63 ± 0.21 pM). Potential specific mercury methylation rates measured in central Lake Erie were 0.062 ± 0.027 day-1, 0.045 ± 0.012 day–1 near the Sandusky Bay input, and 0.031 ± 0.006 day–1 at the Detroit River input (Maumee Bay was below detection; rates were not different; Tukey, p >0.87). Compared to previous work, total mercury concentrations in the western basin observed in this study indicate a decrease of about 3.3% yr–1, which may reflect positive impacts of state, provincial, and national legislation (U.S. National Clean Water Act 1990, Ohio Clean Air and Water Act 2004, Ontario Clean Water Act 2006). However, methylmercury concentrations have increased in western Lake Erie from 2010 to 2019, which may reflect the impact of legacy mercury pollution.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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 teacher head, 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".