Chemical and isotopic constraints on carbon and sulfur dynamics in Lake Erie nearshore waters
Bibliographic record
Abstract
While phosphorus-induced eutrophication has been studied extensively in freshwater ecosystems, cycling of other essential elements such as sulfur and carbon has not been sufficiently explored. To improve our understanding of the carbon and sulfur dynamics across the land-lake interface, concentrations of chloride (Cl), sulfate (SO 4 ), dissolved inorganic carbon (DIC), and dissolved organic carbon (DOC), the stable isotopic compositions of water (d 18 O and d 2 H) and sulfate (d 34 S SO4 and d 18 O SO4 ), and the stable and radio isotopic compositions of DIC (d 13 C DIC and D 14 C DIC ) were measured in water samples from nearshore and offshore sites at Lake Erie, the Detroit River, and other tributaries. The Detroit River and offshore waters were characterized by lower concentrations of Cl and SO 4 but higher values of d 13 C DIC and d 34 S SO4 , whereas other tributaries were featured with higher values of Cl, SO 4 , and d-excess but lower values of d 13 C DIC , D 14 C DIC , d 34 S SO4 , and d 18 O SO4 . The nearshore waters of Lake Erie had elevated values of Cl, SO 4 , and d-excess, and lower values of d 34 S SO4 and d 18 O SO4 than samples from offshore sites, consistently attesting to a strong tributary influence. The average d 34 S SO4 value decreased from the Detroit River to open Lake Erie by as high as 1.5, while there was a concomitant increase in d 18 O SO4 by 2.1. These results revealed that the carbon and sulfur dynamics in Lake Erie nearshore waters were not only affected by tributary inputs but also modulated by a range of in-lake biogeochemical processes such as CO 2 degassing, carbonate precipitation, DOC degradation, microbial sulfate reduction, and subsequent reoxidation.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".