Mercury Export From Freshwater to Estuary: Carbocentric Science Elucidates the Fate of a Toxic Compound in Aquatic Boreal Environments
Bibliographic record
Abstract
The chemistry of mercury in freshwater systems, particularly man-made reservoirs, has received a great deal of attention owing to the high toxicity of the most common organic form, methylmercury. Although methylmercury bioaccumulation in reservoirs and natural lakes has been extensively studied at all latitudes, the fate of the different forms of mercury (total vs. dissolved; organic vs. inorganic) along the entire river-estuary continuum is less well documented. In fact, the difficulty of integrating the numerous parameters involved in mercury speciation in such large study areas, combined with the technical difficulties in sampling and analyzing mercury, have undoubtedly hindered advances in the field. At the same time, carbocentric science has grown exponentially in the last 25 years, and the common fate of carbon and mercury in freshwater has become increasingly clear with time. This literature review, by presenting the knowledge acquired in these two fields, aims to better understand the extent of mercury export from boreal inland waters to estuaries and to investigate the possible downstream ecotoxicological impact of reservoir creation on mercury bioavailability to estuarine food webs and local communities.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".