Geochemical evidence for Alberta Oil Sands contamination in sediments remote to known oil sands deposits in Alberta, Canada
Bibliographic record
Abstract
Oil spills and natural oil seeps are sources of petrogenic hydrocarbons in soils and sediments. To determine the source of hydrocarbon contamination in the environment the geochemical signature of the contaminant needs to be characterised. Here, we present biomarker and other molecular marker diagnostic ratios of Alberta Oil Sands using gas chromatography-mass spectrometry to characterise the deposits and detect their incorporation in surficial sediments. Diagnostic ratios of steranes, terpanes, and aromatic steroids (e.g. C27, C28, and C29 regular sterane abundance, Gammacerane Index, Ts/Tm, TAS/(TAS + MAS), and MPI-2) were measured in samples of Alberta Oil Sands providing a set of criteria for their identification. Seven surficial sediment samples from central and southeast Alberta were then analysed using these criteria to detect Alberta Oil Sands contamination and other petrogenic and pyrogenic source inputs. Geochemical signatures consistent with Alberta Oil Sands hydrocarbons were identified in surficial sediments in Lamont County and glacial sediments from a moraine in Beaver County. Both sites are in Central Alberta, ∼300 km south of any oil sands extraction sites and natural exposures in northern Alberta, indicating long-distance sediment transport processes mobilised the deposits. These results show that the oil sands have been eroded and transported beyond the boundaries of their current known limits. This is important for understanding sediment transport processes as well as for remediation and reclamation purposes.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".