Assessing the effect of deposited bitumen or asphaltenes on the nitrification process in the north saskatchewan river sediment
Bibliographic record
Abstract
Following oil spills, heavier compounds of oils formed oil-sediment mixtures and deposited on the riverbed, yet their impacts on freshwater sediment ecosystems are not well understood. This study aimed to (1) examine the effects of deposited bitumen (Bit) and asphaltene (Asp) on the North Saskatchewan River (NSR) water quality, focusing on organic carbon and nitrogen; (2) assess the impact of Bit or Asp on sedimentary nitrification; and (3) explore the response of the microbial community to Bit or Asp. Laboratory-scale abiotic (no sediment) and biotic treatments with fresh (NH₃-deprived) sediment and NH₃-enriched sediment were performed at 20 ± 1°C for up to 120 days. Results of the abiotic and biotic treatments with fresh sediment indicated that up to 5 mg/L of total organic carbon (TOC) or nitrogen in the form of NH 3 leached from both deposited Asp and Bit into the overlaying water. Considering the relatively low background concentrations of TOC (2.19 ± 0.29 mg/L) and nitrogen (0.07 ± 0.02 mg/L) in the NSR water, the leached compounds could contribute to the overall organic carbon and nitrogen concentrations in the river. A comparison of the unexposed NH 3 -enriched sediment (Ctl) and Bit-exposed NH 3 -enriched sediment showed that exposure of nitrifying communities did not affect ammonia oxidation but decreased nitrite (50 %) and nitrate (30 %) production. Additionally, the sedimentary microbial community composition altered from its initial composition to a new profile post-exposure to Asp or Bit. The microbial communities also responded differently to Bit exposure compared to Asp exposure. For instance, Asp-exposed sediment was dominated by a diverse group of taxa, while Bit-exposed sediment was mainly dominated by phylum Proteobacteria post-exposure. Overall, the findings indicate that deposited Bit and Asp could contribute organic carbon and nitrogen to the NSR water, impaire the sedimentary nitrification process and alter microbial community composition in the sediments.
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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 | 0.000 | 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) | 0.000 | 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".