The Use of Carbon and Nitrogen Stable Isotope Analysis to Characterize Food Web Changes in Aquatic Systems for Reclamation of Oil Sands Process-Affected Materials
Bibliographic record
Abstract
Abstract One strategy for reclamation of oil sands leases in northern Alberta is the construction of lakes and wetlands by capping oil sands process-affected material (OSPM) with water. To assess this approach, experimental sites containing a range of OSPM have been constructed to monitor the evolution of the resulting aquatic habitats. Stable isotopes of carbon and nitrogen were used to assess the effects of OSPM on aquatic food webs. Carbon and nitrogen isotopic signatures of sediment, dissolved inorganic and organic carbon, particulate organic matter, periphyton, plants, plankton, aquatic invertebrates, and fish were used to assess differences related to the naphthenic acid (NA) concentration in OSPM and reference sites. NAs are a principal contaminant of concern in OSPM. Sites were grouped into low (0 to 4 mg/L), medium (4 to 15 mg/L), and high (>15 mg/L) NA concentrations. There were no significant differences in food web area or length among the three NA groupings. In most cases, carbon isotope analyses of samples from low, medium, and high NA concentration sites were not significantly different, suggesting that OSPM is not a significant contributor to food web carbon sources. Significant differences were found in nitrogen isotope signatures between low, medium, and high NA sites. Ammonia from OSPM is suggested as the main contributor to δ15N enrichment.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".