Bibliographic record
Abstract
Wetlands, mainly peatlands, cover more than half of the landscape in northeastern Alberta. Significant efforts are focused on recreating wetland ecosystems within the landscape disturbed by oil sands mining. Early wetland reclamation efforts in the oil sands focussed on constructing marshes using mining byproducts, like tailings – an aqueous solution of silt, sand, clay and residual bitumen, to evaluate the potential of wetlands as water treatment systems. Some marshes developed where water collected in depressions within the reclaimed landscape (“opportunistic wetlands”). The do not contain tailings, although they may be saline if the surrounding soils are sodic. Opportunistic and oil sands process material (OSPM)-affected wetlands, those containing tailings and/or oil sands process water (OSPW), were monitored to determine whether these reclaimed water bodies functioned in a similar manner to natural wetland ecosystems in the region. Recent efforts in wetland reclamation have focused on the following: (1) improving best management practices (i.e. using bioindicators for assessment, habitat design, and revegetation strategies); (2) reclaiming wetland watersheds instead of building individual wetlands in isolation; and (3) design and construction of fen peatlands, the most common wetland type in the region. This paper summarises the history of wetland reclamation in the oil sands region, trends over time in wetland reclamation research, critical findings and the latest wetland reclamation initiatives, such as fen watershed research, design, construction and monitoring.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".