Epilithon isotope composition as an environmental archive in rivers receiving wastewater
Bibliographic record
Abstract
Epilithon is a complex community of autotrophic and heterotrophic organisms that includes inert, organic and inorganic material and is attached to the surface of submersed rocks. Water samples collected in the Grand River (southwestern Ontario) in April 2011 showed that ammonium concentrations decreased downstream, whereas nitrate varied, largely dependent on weather conditions (concentrations of both chemical species were higher during winter). Epilithon δ15N-TN downstream from the Kitchener wastewater treatment plant oscillated between 0.4 to 23.2‰, and δ13C-TC around -27‰. The wastewater treatment plant effluent consisted of δ15N-NO3-between 12 and 16‰, with a decreasing trend as it traveled downstream; δ15N-NH4+became enriched downstream (as high as 31‰). Average values for δ13C-DIC were -10.1‰ and δ13C-DOC -26.8‰. It is proposed that the nitrogen and carbon isotope composition of epilithon could be used as a short- or medium-term environmental archive, as it reflects in-stream processes, such as ammonia oxidation, in a river impacted by treated wastewater. The interpretation provided here was limited due to the ample range of events and potential sources, specifically when the nitrogen isotopic composition of nitrate and ammonium was similar. Epilithon is easily collected, processed and analysed and proved to be valuable tool to describe changes in river and stream geochemistry.
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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".