Mercury speciation and Hg stable isotope ratios in sediments from Amazon floodplain lakes—Brazil
Bibliographic record
Abstract
Abstract Hg concentrations and isotope ratios were measured to better characterize the mercury dynamics related to Hg cycling in Amazon floodplain lakes. We collected sediments, suspended particulate material (SPM), and plankton from floodplain lakes and compared then to sediments from rivers and soils of the central Amazon basin by measuring concentrations of total Hg (THg) and methylmercury (MMHg), and mercury isotope ratios. Concentrations of THg and MMHg in the lake sediments ranged to 69–109 ng g−1 and 0.62–4.78 ng g−1, respectively. A positive correlation between THg and MMHg in soils and sediments suggest that inorganic Hg in this system is highly bioavailable and readily converted to MMHg. δ202Hg values ranged from −1.40‰ to −0.89‰ and Δ199Hg from −0.34‰ to −0.18‰. These values were comparable to those measured in riverine sediments (−2.14‰ to −1.23‰ and −0.51‰ to −0.05‰), suggesting a contribution of riverine sediments to lake sediments, at least during the season of rising waters, during which lake samples were collected. SPM on the other hand was much elevated in THg (590–1066 ng g−1) and showed more negative δ202Hg (−3.00 to −2.15), similar to those found in soils (−2.99‰ to −2.17‰), suggesting that Hg in SPM may originate from erosion of floodplain soils.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".